from collections import defaultdict
from pathlib import Path
import os
import numpy as np
import numpy.matlib
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
import pickle
from pathlib import Path
from deepdiff import DeepDiff
from datetime import date, timedelta
from isoweek import Week
import math
import warnings; warnings.simplefilter('ignore')
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import TimeSeriesSplit
from sklearn.metrics import mean_squared_error
from sklearn.tree import export_graphviz
import graphviz
from statsmodels.tsa.statespace.sarimax import SARIMAX
from statsmodels.graphics.tsaplots import plot_acf
from statsmodels.graphics.tsaplots import plot_pacf
from statsmodels.tsa.stattools import adfuller
import pmdarima as pm
# Set Matplotlib defaults
plt.style.use("seaborn-whitegrid")
plt.rc("figure", autolayout=True, figsize=(11, 5))
plt.rc(
"axes",
labelweight="bold",
labelsize=14,
titleweight="bold",
titlesize=16,
titlepad=10,
)
plot_params = dict(
color="0.75",
style=".-",
markeredgecolor="0.25",
markerfacecolor="0.25",
)
# organize features in each row into 1) static categorical, 2) temporal categorical, 3) temporal continuous
def feature_list(country_id, row):
# Static Categorical
country = country_id #0 country id
# Temporal Categorical (datetime variables)
dt = row[0].to_pydatetime()
year = dt.year #1
month = dt.month #2
day = dt.day #3
week_of_year = dt.isocalendar()[1] #4
day_of_week = row[1].dayow #5
holiday = row[1].holiday #6 holiday
# Temporal Continuous (mobility variables-this will be lagged for srm)
# Temporal Continuous (weather variables)
cloudcover = float(row[1].cloudcover) #13 weather; cloudcover
tempC = float(row[1].tempC) #14 weather; temparature
humidity = float(row[1].humidity) #15 weather; humidity
precipMM = float(row[1].precipMM) #16 weather; precipitation
# Temporal Continuous (vaccination-this will be lagged for srm)
return [country], \
[year, month, day, week_of_year, day_of_week, holiday], \
[cloudcover, tempC, humidity, precipMM] # Static Categorical, Temporal Categorical, Temporal Continuous
# get the input and output sequences from the entire time series
def split_sequences(sequences, timestamp, n_steps_in, n_steps_out):
timestamps = sequences.index
df_time0 = timestamps[0]
df_time_end = timestamps[-1]
dt_steps_in = timedelta(days=n_steps_in)
dt_steps_out = timedelta(days=n_steps_out-1)
dt_1 = timedelta(days=1)
if (timestamp-dt_steps_in>=df_time0) & (timestamp+dt_steps_out<=df_time_end): # if within bounds
# gather input and output parts of the pattern
seq_x = sequences[timestamp-dt_steps_in:timestamp] # input sequence (e.g. previous 14 days)
seq_y = sequences[timestamp+dt_1:timestamp+dt_1+dt_steps_out] # output sequence (e.g. next 7 days including the current timestamp)
return list(seq_x), list(seq_y)
def plot_actual_predicted(rez_dict, dict_country, save_name, n_steps_out=7):
countries = rez_dict.keys()
# plot for each of the 7-day forecast
for country in countries:
fig, ax = plt.subplots(n_steps_out, 1, figsize=(12, 36))
fig.subplots_adjust(wspace=0.5, hspace=0.7)
timestamps = rez_dict[country]['timestamp']
holidays = np.array(dict_country[country].loc[timestamps, 'holiday']==1) # holidays
sundays = np.array(dict_country[country].loc[timestamps, 'dayow']==6) # Sundays
holi_sun = np.logical_or(holidays, sundays)
holiday_timestamps = [date.strftime(i, '%b-%d') for i,v in zip(timestamps ,holi_sun) if v]
y_actual = rez_dict[country]['y']
y_pred = rez_dict[country]['y_pred']
for i in range(n_steps_out):
ts_td = [t+timedelta(days=i) for t in timestamps]
ts = list(map(lambda x:date.strftime(x,'%y-%b-%d'),ts_td))
if save_name is 'train':
interval = 28
elif save_name is 'val':
interval = 14
elif save_name is 'test':
interval = 2
ts_td_interval = [ts for i, ts in enumerate(ts_td) if i in np.arange(0, len(ts_td), interval)]
ts_interval = list(map(lambda x:date.strftime(x,'%y-%b-%d'),ts_td_interval))
ax[i].plot(ts, y_actual[:,i], 'o-')
ax[i].plot(ts, y_pred[:,i], 'o-')
ax[i].xaxis.set_ticks(ts_interval)
ax[i].set_xlabel('Date', fontsize=14, fontweight='bold')
ax[i].set_xlim(ts[0], ts[-1])
ax[i].set_ylabel('Cases per million', fontsize=14, fontweight='bold')
ax[i].set_title(country + '_step_#' + str(i), fontweight='bold', fontsize=20)
ax[i].legend(['y_actual','y_pred'], prop=dict(weight='bold',size=12))
for tick in ax[i].get_xticklabels():
tick.set_rotation(45)
ax[i].tick_params(axis='x', labelsize=12)
ax[i].tick_params(axis='y', labelsize=12)
for holi in holiday_timestamps:
ax[i].axvspan(holi, holi, color='red', alpha=0.3, linewidth=2)
# figure save
fig.savefig(os.path.join('/Users/parkj/Documents/pyDat/dataSet/covid19_forecasting/covid19_figures/sarimax', \
country+'_'+'individual'+'_'+save_name+'_srm_7d.pdf'), tranparent=True)
def split_sequence_features(df_country, ts_curr):
f_rtrc, _ = split_sequences(df_country['rtrc'], ts_curr, n_steps_in=0, n_steps_out=0) # n_steps_in=0, there's no need to lag time series for SARIMAX
f_grph, _ = split_sequences(df_country['grph'], ts_curr, n_steps_in=0, n_steps_out=0)
f_prks, _ = split_sequences(df_country['prks'], ts_curr, n_steps_in=0, n_steps_out=0)
f_tran, _ = split_sequences(df_country['tran'], ts_curr, n_steps_in=0, n_steps_out=0)
f_work, _ = split_sequences(df_country['work'], ts_curr, n_steps_in=0, n_steps_out=0)
f_resi, _ = split_sequences(df_country['resi'], ts_curr, n_steps_in=0, n_steps_out=0)
f_vac, _ = split_sequences(df_country['vac'], ts_curr, n_steps_in=0, n_steps_out=0)
f_case, t_case = split_sequences(df_country['case_mil'], ts_curr, n_steps_in=0, n_steps_out=7)
return f_rtrc, f_grph, f_prks, f_tran, f_work, f_resi, f_vac, f_case, t_case
def split_sequence_features_wo_target(df_country, ts_curr):
f_rtrc, _ = split_sequences(df_country['rtrc'], ts_curr, n_steps_in=0, n_steps_out=0) # n_steps_in=0, there's no need to lag time series for SARIMAX
f_grph, _ = split_sequences(df_country['grph'], ts_curr, n_steps_in=0, n_steps_out=0)
f_prks, _ = split_sequences(df_country['prks'], ts_curr, n_steps_in=0, n_steps_out=0)
f_tran, _ = split_sequences(df_country['tran'], ts_curr, n_steps_in=0, n_steps_out=0)
f_work, _ = split_sequences(df_country['work'], ts_curr, n_steps_in=0, n_steps_out=0)
f_resi, _ = split_sequences(df_country['resi'], ts_curr, n_steps_in=0, n_steps_out=0)
f_vac, _ = split_sequences(df_country['vac'], ts_curr, n_steps_in=0, n_steps_out=0)
f_case, _= split_sequences(df_country['case_mil'], ts_curr, n_steps_in=0, n_steps_out=0)
return f_rtrc, f_grph, f_prks, f_tran, f_work, f_resi, f_vac, f_case
def rmse_y_y_pred(rez_dict, n_steps_out):
rmse_dict = {}
countries = sorted(set(rez_dict['country']))
for country in countries:
country_idx = [cc==country for cc in rez_dict['country']]
country_rmse = []
for d in range(n_steps_out):
country_rmse.append(mean_squared_error(rez_dict['y'][country_idx,d], rez_dict['y_pred'][country_idx,d], squared=False))
rmse_dict[country] = country_rmse
return rmse_dict
def rmse_y_y_pred_country(rez_dict, n_steps_out):
country_rmse = []
for d in range(n_steps_out):
country_rmse.append(mean_squared_error(rez_dict['y'][:,d], rez_dict['y_pred'][:,d], squared=False))
return country_rmse
# preprocess the categorical variables
def simplify_cats(cat_columns):
cat_conv_raw = []
cat_conv_array = np.empty((cat_columns.shape[0],cat_columns.shape[1]))
for c in range(cat_columns.shape[1]):
cat_conv_raw.append(list(cat_columns[:,c]))
raw_vals = np.unique(cat_columns[:,c])
val_map = {}
for i in range(len(raw_vals)):
val_map[raw_vals[i]] = i
cat_conv_array[:,c] = [val_map[j] for j in cat_conv_raw[c]]
return cat_conv_array
# load data from pickle file
filePath_pickle = Path('/Users/parkj/Documents/pyDat/dataSet/covid_country_data.pickle')
with open(filePath_pickle, 'rb') as f:
dict_country = pickle.load(f)
# countries = ['AR', 'AT', 'AU', 'BE', 'CA', 'DE', 'DK', 'FI', 'FR', 'GB', 'ID', 'IE', 'IL', 'IN', 'IT', 'JP', 'KR', 'MX', 'NL', 'NO', 'RU', 'SG', 'US']
train_timestamp = []
train_country = []
train_stat_cat = []
train_temp_cat = []
train_temp_con = []
train_f_rtrc = []
train_f_grph = []
train_f_prks = []
train_f_tran = []
train_f_work = []
train_f_resi = []
train_f_vac = []
train_f_case = []
train_y_unscaled = []
test_timestamp = []
test_country = []
test_stat_cat = []
test_temp_cat = []
test_temp_con = []
test_f_rtrc = []
test_f_grph = []
test_f_prks = []
test_f_tran = []
test_f_work = []
test_f_resi = []
test_f_vac = []
test_f_case = []
test_y_unscaled = []
test_te_timestamp = []
test_te_country = []
test_te_stat_cat = []
test_te_temp_cat = []
test_te_temp_con = []
test_te_f_rtrc = []
test_te_f_grph = []
test_te_f_prks = []
test_te_f_tran = []
test_te_f_work = []
test_te_f_resi = []
test_te_f_vac = []
test_te_f_case = []
n_test = 21 # days
dt_test = timedelta(days=n_test-1)
n_steps_in = 0 # days (# previous cases)
dt_steps_in = timedelta(days=n_steps_in)
n_steps_out = 7 # days (# future cases to be predicted)
dt_steps_out = timedelta(days=n_steps_out-1)
for i, country_key in enumerate(dict_country.keys()):
case_detection = 0
df_country = dict_country[country_key]
df_country.fillna(method='ffill',inplace=True) # forward fill NaNs
df_time0 = df_country.index[0] # the first day of the data
df_time_end = df_country.index[-1] # the last day of the data
# split the df into train and test sets
test_time0 = df_country.index[-1]-dt_test # the first date of test set
train_ind = df_country.index < test_time0 # training index
# feature_list train
df_country_train = df_country.loc[train_ind] # train df
for row in df_country_train.iterrows():
ts_curr = row[0]
# case_mil lagging
if (ts_curr-dt_steps_in>=df_time0) & (ts_curr+dt_steps_out<=df_time_end):
# get feature and target variables
f_rtrc, f_grph, f_prks, f_tran, f_work, f_resi, f_vac, f_case, t_case = split_sequence_features(df_country, ts_curr)
if (case_detection == 0) & (sum(f_case)>0): # to exclude days before 1st case detection
case_detection = 1
if case_detection == 1:
fl_stat_cat, fl_temp_cat, fl_temp_con = feature_list(i, row) # get static categorical, temporal categorical, temporal continuous variables separately
# train data X (for embeddings)
train_country.append(row[1].country_region_code)
train_timestamp.append(ts_curr) # timestamps
train_stat_cat.append(fl_stat_cat) # static categorical
train_temp_cat.append(fl_temp_cat) # temporal categorical
train_temp_con.append(fl_temp_con) # temporal continuous
# train data X (for srm)
train_f_rtrc.append(f_rtrc)
train_f_grph.append(f_grph)
train_f_prks.append(f_prks)
train_f_tran.append(f_tran)
train_f_work.append(f_work)
train_f_resi.append(f_resi)
train_f_vac.append(f_vac)
train_f_case.append(f_case) # case_mil previous days to be used as features
# train data y
train_y_unscaled.append(t_case) # case_mil current & future days to be predicted
# feature list test
df_country_test = df_country.loc[~train_ind] # test df
# feature list test
for row in df_country_test.iterrows():
ts_curr = row[0]
# case_mil lagging
if (ts_curr-dt_steps_in>=df_time0) & (ts_curr+dt_steps_out+timedelta(days=1)<=df_time_end):
# get feature and target variables
f_rtrc, f_grph, f_prks, f_tran, f_work, f_resi, f_vac, f_case, t_case = split_sequence_features(df_country, ts_curr)
fl_stat_cat, fl_temp_cat, fl_temp_con = feature_list(i, row) # get static categorical, temporal categorical, temporal continuous variables separately
# test data X (for embeddings)
test_country.append(row[1].country_region_code)
test_timestamp.append(ts_curr)
test_stat_cat.append(fl_stat_cat) # static categorical
test_temp_cat.append(fl_temp_cat) # temporal categorical
test_temp_con.append(fl_temp_con) # temporal continuous
# test data X (for srm)
test_f_rtrc.append(f_rtrc)
test_f_grph.append(f_grph)
test_f_prks.append(f_prks)
test_f_tran.append(f_tran)
test_f_work.append(f_work)
test_f_resi.append(f_resi)
test_f_vac.append(f_vac)
test_f_case.append(f_case) # case_mil previous days to be used as features
# train data y
test_y_unscaled.append(t_case) # case_mil current & future days to be predicted
elif ts_curr+dt_steps_out+timedelta(days=1)>df_time_end: # get X for tailend trials without target cases
f_rtrc, f_grph, f_prks, f_tran, f_work, f_resi, f_vac, f_case = split_sequence_features_wo_target(df_country, ts_curr)
fl_stat_cat, fl_temp_cat, fl_temp_con = feature_list(i, row)
# tailend test data X (for embeddings)
test_te_country.append(row[1].country_region_code)
test_te_timestamp.append(ts_curr)
test_te_stat_cat.append(fl_stat_cat) # static categorical
test_te_temp_cat.append(fl_temp_cat) # temporal categorical
test_te_temp_con.append(fl_temp_con) # temporal continuous
# tailend test data X (for srm)
test_te_f_rtrc.append(f_rtrc)
test_te_f_grph.append(f_grph)
test_te_f_prks.append(f_prks)
test_te_f_tran.append(f_tran)
test_te_f_work.append(f_work)
test_te_f_resi.append(f_resi)
test_te_f_vac.append(f_vac)
test_te_f_case.append(f_case) # case_mil previous days to be used as features
def matrix_scaler_over_all_columns(input_list, scaler_):
concat_1d = []
for m in input_list:
concat_1d.append(np.reshape(m, (np.shape(m)[0]*np.shape(m)[1],1)))
concat_1d_array = np.concatenate(concat_1d, axis=0)
output_list = []
for m in input_list:
repmat = np.matlib.repmat(concat_1d_array, 1, np.shape(m)[1])
#scaler_ = StandardScaler()
scaler_.fit(repmat)
output_list.append(scaler_.transform(m))
return output_list, scaler_
def matrix_scaler_each_column(input_list, scaler_):
concat = np.concatenate(input_list, axis=0)
scaler_.fit(concat)
output_list = []
for m in input_list:
output_list.append(scaler_.transform(m))
return output_list
# static categorical (country ID)
train_test_stat_cat_simple = simplify_cats(np.concatenate((np.array(train_stat_cat), np.array(test_stat_cat), np.array(test_te_stat_cat)),axis=0))
train_stat_cat_simple = train_test_stat_cat_simple[:len(train_stat_cat)]
test_stat_cat_simple = train_test_stat_cat_simple[len(train_stat_cat):len(train_stat_cat)+len(test_stat_cat)]
test_te_stat_cat_simple = train_test_stat_cat_simple[len(train_stat_cat)+len(test_stat_cat):]
# temporal categorical (date info)
train_test_temp_cat_simple = simplify_cats(np.concatenate((np.array(train_temp_cat), np.array(test_temp_cat), np.array(test_te_temp_cat)),axis=0))
train_temp_cat_simple = train_test_temp_cat_simple[:len(train_temp_cat)]
test_temp_cat_simple = train_test_temp_cat_simple[len(train_temp_cat):len(train_temp_cat)+len(test_temp_cat)]
test_te_temp_cat_simple = train_test_temp_cat_simple[len(train_temp_cat)+len(test_temp_cat):]
# scale temporal continuous (weather info)
temp_con_scaled = matrix_scaler_each_column([train_temp_con, test_temp_con, test_te_temp_con], MinMaxScaler())
train_temp_con_scaled = temp_con_scaled[0]
test_temp_con_scaled = temp_con_scaled[1]
test_te_temp_con_scaled = temp_con_scaled[2]
# scale lagged temporal continuous (for srm)
# rtrc
rtrc_scaled, _ = matrix_scaler_over_all_columns([train_f_rtrc, test_f_rtrc, test_te_f_rtrc], MinMaxScaler())
train_rtrc_scaled = rtrc_scaled[0]
test_rtrc_scaled = rtrc_scaled[1]
test_te_rtrc_scaled = rtrc_scaled[2]
# grph
grph_scaled, _ = matrix_scaler_over_all_columns([train_f_grph, test_f_grph, test_te_f_grph], MinMaxScaler())
train_grph_scaled = grph_scaled[0]
test_grph_scaled = grph_scaled[1]
test_te_grph_scaled = grph_scaled[2]
# prks
prks_scaled, _ = matrix_scaler_over_all_columns([train_f_prks, test_f_prks, test_te_f_prks], MinMaxScaler())
train_prks_scaled = prks_scaled[0]
test_prks_scaled = prks_scaled[1]
test_te_prks_scaled = prks_scaled[2]
# tran
tran_scaled, _ = matrix_scaler_over_all_columns([train_f_tran, test_f_tran, test_te_f_tran], MinMaxScaler())
train_tran_scaled = tran_scaled[0]
test_tran_scaled = tran_scaled[1]
test_te_tran_scaled = tran_scaled[2]
# work
work_scaled, _ = matrix_scaler_over_all_columns([train_f_work, test_f_work, test_te_f_work], MinMaxScaler())
train_work_scaled = work_scaled[0]
test_work_scaled = work_scaled[1]
test_te_work_scaled = work_scaled[2]
# resi
resi_scaled, _ = matrix_scaler_over_all_columns([train_f_resi, test_f_resi, test_te_f_resi], MinMaxScaler())
train_resi_scaled = resi_scaled[0]
test_resi_scaled = resi_scaled[1]
test_te_resi_scaled = resi_scaled[2]
# vac
vac_scaled, _ = matrix_scaler_over_all_columns([train_f_vac, test_f_vac, test_te_f_vac], MinMaxScaler())
train_vac_scaled = vac_scaled[0]
test_vac_scaled = vac_scaled[1]
test_te_vac_scaled = vac_scaled[2]
# case - no need to scale for the SARIMAX model, just use case_per_mil
train_y = np.array(train_y_unscaled)
test_y = np.array(test_y_unscaled)
# concatenate features to get X
train_X = np.concatenate((train_stat_cat_simple, train_temp_cat_simple, train_temp_con_scaled, \
train_rtrc_scaled, train_grph_scaled, train_prks_scaled, train_tran_scaled, \
train_work_scaled, train_resi_scaled, train_vac_scaled, np.array(train_f_case)), axis=1)
test_X = np.concatenate((test_stat_cat_simple, test_temp_cat_simple, test_temp_con_scaled, \
test_rtrc_scaled, test_grph_scaled, test_prks_scaled, test_tran_scaled, \
test_work_scaled, test_resi_scaled, test_vac_scaled, np.array(test_f_case)), axis=1)
test_te_X = np.concatenate((test_te_stat_cat_simple, test_te_temp_cat_simple, test_te_temp_con_scaled, \
test_te_rtrc_scaled, test_te_grph_scaled, test_te_prks_scaled, test_te_tran_scaled, \
test_te_work_scaled, test_te_resi_scaled, test_te_vac_scaled, np.array(test_te_f_case)), axis=1)
all_X = np.concatenate((train_X, test_X, test_te_X), axis=0)
print("Number of train datapoints: ", len(train_y))
print("Number of test datapoints: ", len(test_y))
Number of train datapoints: 12670 Number of test datapoints: 322
def feaure_name_list_append(list_to_append, count, namebase, backward=False):
for i in range(count):
if backward==False:
name_to_append = namebase + str(i+1)
elif backward==True:
name_to_append = namebase + str(count-i)
list_to_append.append(name_to_append)
return list_to_append
feature_name_list = []
# static categorical
feature_name_list.append('country')
# temporal categorical
feature_name_list.append('year')
feature_name_list.append('month')
feature_name_list.append('dayom')
feature_name_list.append('weekoy')
feature_name_list.append('dayoy')
feature_name_list.append('holid')
# temporal continuous
feaure_name_list_append(feature_name_list, 4, 'weather', backward=False)
# rtrc
feaure_name_list_append(feature_name_list, 1, 'rtrc', backward=True)
# grph
feaure_name_list_append(feature_name_list, 1, 'grph', backward=True)
# prks
feaure_name_list_append(feature_name_list, 1, 'prks', backward=True)
# tran
feaure_name_list_append(feature_name_list, 1, 'tran', backward=True)
# work
feaure_name_list_append(feature_name_list, 1, 'work', backward=True)
# resi
feaure_name_list_append(feature_name_list, 1, 'resi', backward=True)
# vac
feaure_name_list_append(feature_name_list, 1, 'vac', backward=True)
# case
feaure_name_list_append(feature_name_list, 1, 'case', backward=True)
['country', 'year', 'month', 'dayom', 'weekoy', 'dayoy', 'holid', 'weather1', 'weather2', 'weather3', 'weather4', 'rtrc1', 'grph1', 'prks1', 'tran1', 'work1', 'resi1', 'vac1', 'case1']
A classic approach in timeseries forecasting provides a parsimonious desciption of a (weakly) stationary stochastic process in terms of polynomials, one for the autoregression (AR) and the second for the moving average (MA), thus the name 'ARMA' model. ARMA has been extended to better incorporate seasonality (S) in the timeseries and to include exogenous (X) variables to leverage the prediction power of the model. SARIMAX model provides a framework where a timeseries can be forcasted based on 1) autoregressive, 2) moving-average, 3) seasonal, 4) exogenous components. Thus, here we use SARIMAX model to forecast COVID19 cases for days and weeks into the future. Here, we perform an EDA to get an insight for the range of key parameters that would be used in the automatic grid search of best parameters in the next session.
# EDA to estimate parameters for SARIMAX
train_X_us = train_X[[country=='US' for country in train_country],:]
us_case = train_X_us[:,-1]
# Dicky-Fuller test for stationarity
adf_rez = adfuller(us_case)
print("p-value for Dickey-Fuller test of stationarity is {0:.4f}, meaning that the time series is non-stationary".format(adf_rez[1]))
p-value for Dickey-Fuller test of stationarity is 0.5333, meaning that the time series is non-stationary
# differencing and log transform
us_case_log = np.log(10+us_case)
us_case_log_diff = np.diff(np.log(10+us_case)) # add 10 to avoid log(0) or log(nagatives)
# Dicky-Fuller test for stationarity
adf_rez1 = adfuller(us_case_log_diff)
print("p-value for Dickey-Fuller test of stationarity is {0:.4f}, thus we can reject the null hypothesis that the time series is non-stationary".format(adf_rez1[1]))
p-value for Dickey-Fuller test of stationarity is 0.0009, thus we can reject the null hypothesis that the time series is non-stationary
# use auto-correlation function (ACF) and partial ACF to estimate the orders of the AR and MA components in the SARIMAX model
fig = plt.figure(figsize=(10,5))
ax = fig.add_subplot(1,1,1)
fig = plot_acf(us_case_log_diff, lags=21, ax=ax)
ax.tick_params(axis='x', labelsize=14)
ax.tick_params(axis='y', labelsize=14)
ax.set_xlabel('Day', fontsize=16)
ax.set_ylabel('Coefficient', fontsize=16)
ax.set_ylim([-1.05,1.05])
plt.show()
plot_pacf(us_case_log_diff, lags=21)
plt.show()
There is a clear seasonality with period=7 observed reflecting the weekly fluctuations, suggesting that SARIMA would be the better model than ARIMA.
Try grid searching to estimate parameters for SARIMA
# use pmdarima for an automatic specification of SARIMAX parameters
auto_model = pm.auto_arima(us_case_log,
seasonal=True, m=7,
d=1, D=1,
start_p=0, start_q=0,
max_p=2, max_q=2,
max_P=2, max_Q=2,
trace=True,
error_action='ignore',
suppress_warnings=True)
Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-305.217, Time=0.17 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-146.841, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-463.271, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-490.426, Time=0.25 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-365.070, Time=0.17 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-488.654, Time=0.38 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-488.627, Time=0.46 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-467.576, Time=0.23 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-486.765, Time=1.56 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-303.621, Time=0.13 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-507.073, Time=0.33 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-381.182, Time=0.12 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-505.227, Time=0.66 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-505.221, Time=0.59 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-482.099, Time=0.33 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-503.257, Time=1.19 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-487.501, Time=0.19 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=inf, Time=1.68 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-509.909, Time=1.15 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-397.296, Time=0.24 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-507.953, Time=1.23 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-507.329, Time=2.18 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-480.367, Time=0.36 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-506.420, Time=2.54 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-507.497, Time=0.40 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-505.919, Time=0.65 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-506.843, Time=2.57 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 20.016 seconds
# Create a SARIMAX model
model = SARIMAX(us_case_log, order=auto_model.order, seasonal_order=auto_model.seasonal_order, \
exog = train_X_us[:,1:len(feature_name_list)-1])
# Fit the model
model_fit = model.fit()
log_yhat = model_fit.predict()
# reverse the log transform and addition of constant
yhat = np.exp(log_yhat)-10
plt.plot(us_case, label='US cases (y)')
plt.plot(yhat, label='predicted cases (yhat)')
plt.legend()
plt.xlabel('Time points (day)')
plt.ylabel('Cases per million')
plt.show()
The above plot shows that the SARIMAX fits the actual case data pretty well.
print(model_fit.summary())
SARIMAX Results
===========================================================================================
Dep. Variable: y No. Observations: 554
Model: SARIMAX(1, 1, 2)x(0, 1, [1], 7) Log Likelihood 320.718
Date: Wed, 17 Nov 2021 AIC -597.435
Time: 15:25:16 BIC -502.778
Sample: 0 HQIC -560.433
- 554
Covariance Type: opg
==============================================================================
coef std err z P>|z| [0.025 0.975]
------------------------------------------------------------------------------
x1 -32.8411 10.228 -3.211 0.001 -52.888 -12.794
x2 -2.7350 0.852 -3.211 0.001 -4.405 -1.065
x3 -0.0923 0.028 -3.332 0.001 -0.147 -0.038
x4 0.0024 0.002 1.304 0.192 -0.001 0.006
x5 -3.155e-09 1.7e-06 -0.002 0.999 -3.34e-06 3.33e-06
x6 -0.0399 0.035 -1.140 0.254 -0.108 0.029
x7 0.0337 0.033 1.033 0.302 -0.030 0.098
x8 0.0440 0.076 0.576 0.565 -0.106 0.194
x9 -0.0153 0.068 -0.226 0.821 -0.148 0.117
x10 -0.0860 0.128 -0.672 0.502 -0.337 0.165
x11 0.4062 0.263 1.545 0.122 -0.109 0.922
x12 0.3350 0.398 0.842 0.400 -0.445 1.115
x13 0.0634 0.466 0.136 0.892 -0.850 0.977
x14 -0.7711 0.456 -1.690 0.091 -1.665 0.123
x15 1.5627 0.458 3.409 0.001 0.664 2.461
x16 -0.1962 0.460 -0.426 0.670 -1.098 0.706
x17 13.0304 4.743 2.747 0.006 3.734 22.327
ar.L1 -0.8971 0.060 -14.925 0.000 -1.015 -0.779
ma.L1 0.3706 0.074 5.037 0.000 0.226 0.515
ma.L2 -0.3676 0.056 -6.565 0.000 -0.477 -0.258
ma.S.L7 -0.3877 0.035 -11.005 0.000 -0.457 -0.319
sigma2 0.0179 0.001 22.875 0.000 0.016 0.019
===================================================================================
Ljung-Box (L1) (Q): 0.60 Jarque-Bera (JB): 432.17
Prob(Q): 0.44 Prob(JB): 0.00
Heteroskedasticity (H): 1.91 Skew: 0.39
Prob(H) (two-sided): 0.00 Kurtosis: 7.29
===================================================================================
Warnings:
[1] Covariance matrix calculated using the outer product of gradients (complex-step).
[2] Covariance matrix is singular or near-singular, with condition number 1.96e+19. Standard errors may be unstable.
The model summary shows that autoregressive (AR) and moving average (MA) components of the model appeared to be highly significant as expected. As well some of the exogenous variables like 'vaccination', 'mobility in workplace', and temporal categorical (year, month, dayofm) were significant features for the model. Now let's go ahead and try forecasting with SARIMAX model for all countries.
def country_train_data_sum(country_dict, n_steps_out):
y_pred_fold = np.empty((len(country_dict['train_idx_country_fold'][0]), n_steps_out, len(country_dict['train_preds_fold'])))
y_pred_fold[:] = np.NaN
for i, idx in enumerate(country_dict['train_idx_country_fold']):
y_pred_fold[idx,:,i] = country_dict['train_preds_fold'][i]
country_dict['train_y_pred'] = np.nanmean(y_pred_fold, axis=2)
train_set_idx = np.isnan(country_dict['train_y_pred']).sum(axis=1)==0
country_dict['y'] = train_y[train_set_idx,:] # back to the original unit (cases per million)
country_dict['y_pred'] = country_dict['train_y_pred'][train_set_idx,:]
country_dict['rmse'] = rmse_y_y_pred_country(country_dict, n_steps_out)
country_dict['X'] = train_X[train_set_idx,:]
country_dict['timestamp'] = [train_timestamp[i] for i, logic in enumerate(train_set_idx) if logic ==True]
return country_dict
def country_validation_data_sum(country_dict, n_steps_out):
y_pred_fold = np.empty((len(country_dict['val_idx_country_fold'][0]), n_steps_out, len(country_dict['val_preds_fold'])))
y_pred_fold[:] = np.NaN
for i, idx in enumerate(country_dict['val_idx_country_fold']):
y_pred_fold[idx,:,i] = country_dict['val_preds_fold'][i]
country_dict['val_y_pred'] = np.nanmean(y_pred_fold, axis=2)
val_set_idx = np.isnan(country_dict['val_y_pred']).sum(axis=1)==0
country_dict['y'] = train_y[val_set_idx,:] # back to the original unit (cases per million)
country_dict['y_pred'] = country_dict['val_y_pred'][val_set_idx,:]
country_dict['rmse'] = rmse_y_y_pred_country(country_dict, n_steps_out)
country_dict['X'] = train_X[val_set_idx,:]
country_dict['timestamp'] = [train_timestamp[i] for i, logic in enumerate(val_set_idx) if logic ==True]
return country_dict
def country_test_data_sum(country_dict, n_steps_out):
y_pred_fold = np.empty((len(country_dict['test_idx_country_fold'][0]), n_steps_out, len(country_dict['test_preds_fold'])))
y_pred_fold[:] = np.NaN
for i, idx in enumerate(country_dict['test_idx_country_fold']):
y_pred_fold[idx,:,i] = country_dict['test_preds_fold'][i]
country_dict['test_y_pred'] = np.nanmean(y_pred_fold, axis=2)
test_set_idx = np.isnan(country_dict['test_y_pred']).sum(axis=1)==0
country_dict['y'] = test_y[test_set_idx,:] # back to the original unit (cases per million)
country_dict['y_pred'] = country_dict['test_y_pred'][test_set_idx,:]
country_dict['rmse'] = rmse_y_y_pred_country(country_dict, n_steps_out)
country_dict['X'] = test_X[test_set_idx,:]
country_dict['timestamp'] = [test_timestamp[i] for i, logic in enumerate(test_set_idx) if logic ==True]
return country_dict
def SARIMAX_grid_search(timeseries, exogenous, seasonal_diff=7):
# use pmdarima for an automatic specification of SARIMAX parameters
auto_model = pm.auto_arima(timeseries,
seasonal=True, m=seasonal_diff,
d=1, D=1,
start_p=0, start_q=0,
max_p=2, max_q=2,
max_P=2, max_Q=2,
trace=True,
error_action='ignore',
suppress_warnings=True) # m is the period for seasonal differencing
# Create a SARIMAX model
model = SARIMAX(timeseries, order=auto_model.order, seasonal_order=auto_model.seasonal_order, \
exog = exogenous)
# Fit the model
model_fit = model.fit()
return model_fit
def prepare_exog(train_end_timestamp, entire_timestamp, country_idx, X, steps):
ts_steps_out = [train_end_timestamp+timedelta(days=i+1) for i in range(steps)]
ts_steps_out_idx = [ts in ts_steps_out for ts in entire_timestamp]
X_steps_out = X[np.array(ts_steps_out_idx) & np.array(country_idx),:]
return X_steps_out
def sarimax_output_organize(timeseries, len_timeseries, n_steps_out):
output_array = np.empty((len_timeseries, n_steps_out))
for i in range(n_steps_out):
output_array[:,n_steps_out-1-i] = timeseries[np.arange(-len_timeseries-i,-i)]
return output_array
# get the walk-forward validation folds for train and validation sets
train_folds = []
validation_folds = []
# get the timestamps for train and validation folds
sorted_train_timestamp = sorted((set(train_timestamp))) # unique timestamps in the train set
tscv = TimeSeriesSplit(n_splits=5, test_size=n_test) # split train and validations sets for cross validation
for train_idx, validation_idx in tscv.split(sorted_train_timestamp): # get train and validation sets
# print("TRAIN:", train_idx, "VALIDATION:", validation_idx)
train_folds.append([sorted_train_timestamp[i] for i in train_idx]) # folds in train set
validation_folds.append([sorted_train_timestamp[i] for i in validation_idx]) # folds in validation set
train_preds = []
val_preds = []
test_preds = []
train_preds = []
val_preds = []
test_preds = []
country_list = list(set(train_country))
country_list.sort()
rez_country_srm_7d_train = {}
rez_country_srm_7d_val = {}
rez_country_srm_7d_test = {}
all_timestamps = train_timestamp+test_timestamp+test_te_timestamp # entire timestamps
# train and test the model with cross validation
for country in country_list:
rez_country_srm_7d_train[country] = {}
rez_country_srm_7d_val[country] = {}
rez_country_srm_7d_test[country] = {}
# train & validation sets
country_idx = list(map(lambda x: x==country, train_country))
# test set (doesn't change across folds)
country_idx_test = list(map(lambda x: x==country, test_country))
X_test_country = test_X[country_idx_test,:]
test_ts = [ts for i, ts in enumerate(test_timestamp) if country_idx_test[i]]
# test tailend set (doesn't change across folds)
country_idx_test_te = list(map(lambda x: x==country, test_te_country))
X_test_te_country = test_te_X[country_idx_test_te,:]
test_te_ts = [ts for i, ts in enumerate(test_te_timestamp) if country_idx_test_te[i]]
all_country_idx = country_idx+country_idx_test+country_idx_test_te
train_preds_c_f = []
train_y_c_f = []
train_idx_c_f = []
val_preds_c_f = []
val_y_c_f = []
val_idx_c_f = []
test_preds_c_f = []
test_y_c_f = []
test_idx_c_f = []
rez_country_srm_7d_train[country] = {}
rez_country_srm_7d_val[country] = {}
rez_country_srm_7d_test[country] = {}
for fold in range(len(train_folds)): # iterate cross-validation folds
fold_idx_train = [ts in train_folds[fold] for ts in train_timestamp]
fold_idx_val = [ts in validation_folds[fold] for ts in train_timestamp]
train_idx_c_f.append(list(np.array(fold_idx_train) & np.array(country_idx)))
val_idx_c_f.append(list(np.array(fold_idx_val) & np.array(country_idx)))
test_idx_c_f.append(country_idx_test)
X_train_c_f, X_val_c_f = train_X[train_idx_c_f[fold],:], train_X[val_idx_c_f[fold],:] # X_train for the current country, fold
train_y_c_f.append(train_y[train_idx_c_f[fold],:]) # train y for this country and fold
val_y_c_f.append(train_y[val_idx_c_f[fold],:]) # validation y for this country and fold
test_y_c_f.append(test_y[country_idx_test,:])
# prepare exogenous variables to be used for SARIMAX forecasting
train_ts_c_f = [train_timestamp[i] for i in range(len(train_timestamp)) if train_idx_c_f[fold][i]] # timestamps of the current folder, country
train_end = train_ts_c_f[-1] # the latest timepoint of the training set
train_exog_steps_out = timedelta(days=n_steps_out).days
train_exog = prepare_exog(train_end, train_timestamp, country_idx, train_X, train_exog_steps_out) # exogenous variables over days
val_ts_c_f = [train_timestamp[i] for i in range(len(train_timestamp)) if val_idx_c_f[fold][i]] # timestamps of the current folder, country
val_exog_steps_out = (val_ts_c_f[-1]+timedelta(days=n_steps_out)-train_end).days #USE CAUTION HERE! timedelta(days=n_steps_out+n_test-1).days
val_exog = prepare_exog(train_end, all_timestamps, all_country_idx, all_X, val_exog_steps_out) # exogenous variables over days
test_exog_steps_out = (test_ts[-1]+timedelta(days=n_steps_out)-train_end).days
test_exog = prepare_exog(train_end, all_timestamps, all_country_idx, all_X, test_exog_steps_out)
y_train_pred_c_f = np.empty((train_y_c_f[fold].shape[0], n_steps_out))
y_val_pred_c_f = np.empty((val_y_c_f[fold].shape[0], n_steps_out))
y_test_pred_c_f = np.empty((X_test_country.shape[0], n_steps_out))
# SARIMAX model fit
x_log_train = np.log(X_train_c_f[:,-1]+10) # add a constant and log transform the case_per_mil
x_exog_train = X_train_c_f[:,1:len(feature_name_list)-1] # exogenous variables for model fitting
x_exog_train_predict = train_exog[:,1:len(feature_name_list)-1] # exogenous variables for forecasting the training set
x_exog_val_predict = val_exog[:,1:len(feature_name_list)-1] # exogenous variables for forecasting the validation set
x_exog_test_predict = test_exog[:,1:len(feature_name_list)-1] # # exogenous variables for forecasting the test set
# grid search SARIMAX parameters
sarimax_model = SARIMAX_grid_search(x_log_train, x_exog_train, seasonal_diff=7)
# predict train data and inverse transform
model_y_train = np.exp(sarimax_model.predict())-10
# forecast train data
train_y_forecast = np.exp(sarimax_model.forecast(train_exog_steps_out, exog=x_exog_train_predict))-10
model_train_y_forecast = np.concatenate((model_y_train, train_y_forecast), axis=0)
y_train_pred_c_f = sarimax_output_organize(model_train_y_forecast, train_y_c_f[fold].shape[0], 7)
# forecast validation data
val_y_forecast = np.exp(sarimax_model.forecast(val_exog_steps_out, exog=x_exog_val_predict))-10
y_val_pred_c_f = sarimax_output_organize(val_y_forecast, val_y_c_f[fold].shape[0], 7)
# forecast test data
test_y_forecast = np.exp(sarimax_model.forecast(test_exog_steps_out, exog=x_exog_test_predict))-10
y_test_pred_c_f = sarimax_output_organize(test_y_forecast, test_y_c_f[fold].shape[0], 7)
train_preds_c_f.append(y_train_pred_c_f)
val_preds_c_f.append(y_val_pred_c_f)
test_preds_c_f.append(y_test_pred_c_f)
if fold==len(train_folds)-1:
rez_country_srm_7d_train[country]['model'] = sarimax_model # save the model once per country (last fold, one-step prediction)
print('Completed fold #{0:d} of country {1:s}'.format(fold+1, country))
# rez dictionary for train
rez_country_srm_7d_train[country]['train_preds_fold'] = train_preds_c_f
rez_country_srm_7d_train[country]['train_idx_country_fold'] = train_idx_c_f
rez_country_srm_7d_train[country]['train_y_fold'] = train_y_c_f
rez_country_srm_7d_train[country] = country_train_data_sum(rez_country_srm_7d_train[country], n_steps_out) # 'y', 'y_pred', 'rmse', 'X', 'timestamp'
# rez dictionary for validation
rez_country_srm_7d_val[country]['val_preds_fold'] = val_preds_c_f
rez_country_srm_7d_val[country]['val_idx_country_fold'] = val_idx_c_f
rez_country_srm_7d_val[country]['val_y_fold'] = val_y_c_f
rez_country_srm_7d_val[country] = country_validation_data_sum(rez_country_srm_7d_val[country], n_steps_out) # 'y', 'y_pred', 'rmse', 'X', 'timestamp'
# rez dictionary for test
rez_country_srm_7d_test[country]['test_preds_fold'] = test_preds_c_f
rez_country_srm_7d_test[country]['test_idx_country_fold'] = test_idx_c_f
rez_country_srm_7d_test[country]['test_y_fold'] = test_y_c_f
rez_country_srm_7d_test[country] = country_test_data_sum(rez_country_srm_7d_test[country], n_steps_out) # 'y', 'y_pred', 'rmse', 'X', 'timestamp'
Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=99.867, Time=0.27 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=401.844, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=101.721, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-71.170, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=165.156, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-69.494, Time=0.43 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-69.487, Time=0.94 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=46.436, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-67.640, Time=1.10 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=103.828, Time=0.19 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-69.966, Time=0.40 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-69.774, Time=0.41 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-30.769, Time=0.22 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-71.812, Time=0.88 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=156.629, Time=0.25 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-69.835, Time=1.85 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-69.834, Time=2.47 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=46.127, Time=0.52 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-67.877, Time=2.92 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-70.055, Time=1.09 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-71.763, Time=0.74 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-66.305, Time=1.30 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 16.814 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country AR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=89.367, Time=0.29 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=407.499, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=98.963, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-83.977, Time=0.36 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=169.345, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-82.420, Time=0.49 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-82.416, Time=0.91 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=43.389, Time=0.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-80.542, Time=0.93 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=93.519, Time=0.22 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-82.380, Time=0.51 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-82.286, Time=0.76 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-41.232, Time=0.26 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-84.198, Time=1.22 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=161.189, Time=0.30 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-82.264, Time=1.50 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-82.265, Time=3.34 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=43.375, Time=0.61 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-80.316, Time=3.73 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-82.436, Time=1.58 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-84.009, Time=0.72 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-78.504, Time=1.64 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 19.983 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country AR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=82.508, Time=0.30 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=412.513, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=97.578, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-91.283, Time=0.32 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=167.737, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-89.681, Time=0.55 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-89.676, Time=0.78 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=39.313, Time=0.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-87.991, Time=1.46 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=87.052, Time=0.22 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-89.551, Time=0.59 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-89.490, Time=0.58 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-48.400, Time=0.31 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-91.193, Time=1.26 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-89.506, Time=1.14 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 8.091 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country AR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=69.857, Time=0.33 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=417.702, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=90.971, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-109.793, Time=0.40 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=168.208, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-108.221, Time=0.51 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-108.221, Time=0.77 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=30.796, Time=0.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-106.435, Time=0.95 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=74.447, Time=0.23 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-107.968, Time=0.54 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-107.928, Time=0.51 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-64.764, Time=0.32 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-109.654, Time=1.41 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-108.200, Time=0.70 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 7.270 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country AR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=55.790, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=416.012, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=75.731, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-131.972, Time=0.40 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=157.700, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-130.442, Time=0.48 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-130.437, Time=0.82 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=13.430, Time=0.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-128.716, Time=0.87 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=60.348, Time=0.27 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-130.165, Time=0.62 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-130.121, Time=0.52 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-85.007, Time=0.36 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-131.920, Time=1.48 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-130.532, Time=0.71 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 7.550 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country AR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-128.795, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=101.712, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-137.895, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-237.514, Time=0.27 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-73.423, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-244.145, Time=0.40 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-157.957, Time=0.16 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-244.405, Time=0.81 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-185.315, Time=0.44 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-241.660, Time=1.08 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-244.283, Time=1.45 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=-128.674, Time=0.63 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-249.614, Time=1.45 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-249.651, Time=0.79 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-243.007, Time=0.53 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-163.883, Time=0.21 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-249.468, Time=2.17 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-80.687, Time=0.21 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-248.089, Time=0.93 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-190.790, Time=0.56 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-246.993, Time=1.19 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-232.220, Time=0.41 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-250.159, Time=0.92 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-242.831, Time=0.59 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-165.516, Time=0.38 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-250.062, Time=1.87 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-249.968, Time=2.46 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-84.908, Time=0.13 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-248.450, Time=1.13 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-192.037, Time=0.75 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-247.651, Time=3.49 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-250.536, Time=0.62 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-244.153, Time=0.42 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-163.905, Time=0.30 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-250.278, Time=1.45 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-250.272, Time=2.33 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-77.626, Time=0.09 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-249.130, Time=1.22 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-192.301, Time=0.36 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-247.777, Time=1.29 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-249.276, Time=1.15 sec Best model: ARIMA(2,1,0)(1,1,1)[7] Total fit time: 35.244 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country AT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-142.147, Time=0.23 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=101.621, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-153.872, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-257.558, Time=0.29 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-82.767, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-262.716, Time=0.55 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-174.829, Time=0.17 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-263.683, Time=0.88 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-203.140, Time=0.39 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-261.694, Time=3.35 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-263.447, Time=1.97 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=-142.561, Time=0.62 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-269.244, Time=1.24 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-268.640, Time=0.81 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-208.555, Time=0.64 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-267.022, Time=2.90 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-180.740, Time=0.26 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-268.982, Time=1.93 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-251.124, Time=0.93 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-269.691, Time=2.24 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-269.203, Time=0.98 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-209.778, Time=0.59 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-267.573, Time=3.38 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-182.219, Time=0.82 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-269.520, Time=2.83 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-269.940, Time=1.46 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-269.661, Time=0.65 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-209.940, Time=0.54 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-267.982, Time=2.87 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-180.425, Time=0.22 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-269.877, Time=3.43 sec ARIMA(2,1,0)(2,1,1)[7] intercept : AIC=-269.142, Time=3.23 sec Best model: ARIMA(2,1,0)(2,1,1)[7] Total fit time: 40.732 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country AT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-155.221, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=101.069, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-166.229, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-275.937, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-89.903, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-280.165, Time=0.51 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-187.993, Time=0.19 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-280.826, Time=0.95 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-219.972, Time=0.36 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-278.928, Time=2.79 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-280.754, Time=1.89 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=-155.212, Time=0.77 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-286.214, Time=1.47 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-285.880, Time=0.59 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-225.198, Time=0.61 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-284.250, Time=3.05 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-193.725, Time=0.30 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-286.089, Time=2.31 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-267.464, Time=1.20 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-286.335, Time=1.83 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-286.092, Time=0.85 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-226.102, Time=0.85 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-283.728, Time=3.65 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-194.641, Time=0.60 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-286.304, Time=2.98 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-286.350, Time=1.29 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-286.338, Time=0.76 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-226.119, Time=0.51 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-284.494, Time=3.22 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-192.497, Time=0.31 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-286.432, Time=2.51 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-285.327, Time=1.16 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-282.246, Time=0.44 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=-267.264, Time=2.25 sec ARIMA(2,1,0)(1,1,2)[7] intercept : AIC=-281.836, Time=3.58 sec Best model: ARIMA(2,1,0)(1,1,2)[7] Total fit time: 44.705 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country AT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-163.707, Time=0.23 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=97.374, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-170.922, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-279.444, Time=0.36 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-96.655, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-287.691, Time=0.50 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-191.996, Time=0.18 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.88 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.72 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-285.622, Time=0.86 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-222.389, Time=0.41 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=2.79 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-293.161, Time=1.51 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-285.136, Time=0.49 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-197.630, Time=0.30 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-293.890, Time=1.79 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-227.575, Time=0.54 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-291.927, Time=3.01 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.59 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-276.633, Time=1.01 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-294.043, Time=2.40 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-293.444, Time=1.23 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-228.876, Time=0.79 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-291.845, Time=3.49 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-198.816, Time=0.47 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=2.93 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-294.654, Time=1.26 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-294.272, Time=0.69 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-229.536, Time=0.35 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-292.823, Time=3.28 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-197.462, Time=0.28 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=2.32 sec ARIMA(2,1,0)(2,1,1)[7] intercept : AIC=-292.988, Time=3.58 sec Best model: ARIMA(2,1,0)(2,1,1)[7] Total fit time: 43.629 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country AT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-188.789, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=85.637, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-192.379, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-307.302, Time=0.41 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-111.535, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-316.225, Time=0.63 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-213.822, Time=0.37 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.28 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.99 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-313.910, Time=0.95 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-246.027, Time=0.37 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=3.93 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-321.648, Time=0.88 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-312.943, Time=0.51 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-219.346, Time=0.31 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-323.014, Time=1.60 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-250.997, Time=0.70 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-320.637, Time=3.17 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.69 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-305.105, Time=1.00 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-323.227, Time=2.24 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-321.991, Time=1.23 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-252.253, Time=0.90 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-320.367, Time=3.61 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-220.618, Time=0.50 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=2.76 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-323.743, Time=1.48 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-322.768, Time=0.79 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-252.893, Time=0.62 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=inf, Time=3.26 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-219.353, Time=0.26 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=2.52 sec ARIMA(2,1,0)(2,1,1)[7] intercept : AIC=-321.963, Time=3.54 sec Best model: ARIMA(2,1,0)(2,1,1)[7] Total fit time: 45.239 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country AT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.41 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-453.023, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-709.573, Time=0.52 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.67 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-580.218, Time=0.15 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-765.110, Time=0.59 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.08 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.62 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-661.099, Time=0.21 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-818.400, Time=0.50 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-767.227, Time=0.39 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=1.98 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.29 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-818.017, Time=0.90 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-802.807, Time=0.70 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-816.541, Time=1.49 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 12.536 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country AU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.43 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-495.731, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-764.931, Time=0.24 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.99 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-629.261, Time=0.10 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-823.275, Time=0.57 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.45 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.65 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-714.288, Time=0.29 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-879.079, Time=0.47 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-825.266, Time=0.41 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.37 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.23 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-878.770, Time=1.03 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-862.822, Time=0.71 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-877.174, Time=2.19 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 13.165 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country AU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.47 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-539.433, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-821.172, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.79 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-679.256, Time=0.15 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-882.309, Time=0.55 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.61 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.74 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-768.058, Time=0.23 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-940.642, Time=0.54 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-884.143, Time=0.62 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=1.86 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.34 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-940.374, Time=1.07 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-923.658, Time=0.75 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-938.710, Time=1.52 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 12.582 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country AU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.41 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-578.359, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-872.496, Time=0.42 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=1.05 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-723.202, Time=0.18 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-935.556, Time=0.52 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.73 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.70 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-817.762, Time=0.32 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-994.584, Time=0.82 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-936.468, Time=0.45 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.37 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.26 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-994.063, Time=1.05 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-977.213, Time=0.89 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-992.589, Time=2.17 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 14.415 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country AU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.67 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-616.949, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-918.985, Time=0.38 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.97 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-763.409, Time=0.14 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-986.460, Time=0.56 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.46 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.78 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-865.554, Time=0.41 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-1046.698, Time=0.81 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-984.321, Time=0.55 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.34 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.26 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-1046.569, Time=1.19 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-1030.048, Time=0.72 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-1044.698, Time=1.64 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 14.912 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country AU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=599.825, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=827.321, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=624.239, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=426.202, Time=0.38 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=605.714, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=422.565, Time=0.42 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=528.882, Time=0.16 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=424.553, Time=0.92 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=424.551, Time=1.37 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=422.587, Time=0.81 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=492.463, Time=0.27 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=426.555, Time=0.73 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=423.193, Time=0.56 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=422.612, Time=0.43 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=497.803, Time=0.30 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=410.767, Time=1.80 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=409.724, Time=1.34 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=609.694, Time=0.26 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=410.674, Time=2.99 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=528.723, Time=0.70 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=inf, Time=3.35 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=425.792, Time=0.46 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=426.525, Time=0.52 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=411.974, Time=1.21 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=423.456, Time=0.60 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=413.761, Time=1.85 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 21.965 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country BE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=611.858, Time=0.24 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=852.581, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=641.518, Time=0.12 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=431.853, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=624.330, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=428.459, Time=0.39 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=541.765, Time=0.16 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=430.438, Time=0.80 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=430.436, Time=1.25 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=428.452, Time=0.94 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=611.661, Time=0.55 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=429.420, Time=1.26 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=429.011, Time=1.28 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=506.518, Time=0.71 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=416.585, Time=3.21 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=415.542, Time=1.25 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=628.148, Time=0.23 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=416.675, Time=1.85 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=542.815, Time=0.66 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=419.075, Time=3.60 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=431.969, Time=0.50 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=432.514, Time=0.66 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=417.106, Time=1.63 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=429.641, Time=0.69 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=428.422, Time=2.18 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 24.611 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country BE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=656.647, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=896.058, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=674.886, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=466.389, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=669.400, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=462.908, Time=0.45 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=579.420, Time=0.19 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=464.897, Time=0.82 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=464.897, Time=1.78 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=462.936, Time=0.96 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=539.896, Time=0.38 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=466.898, Time=0.91 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=463.469, Time=0.55 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=462.986, Time=0.68 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=541.029, Time=0.32 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=452.713, Time=2.10 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=451.720, Time=1.34 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=673.330, Time=0.30 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=452.627, Time=3.25 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=580.745, Time=0.69 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=455.618, Time=3.71 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=466.012, Time=0.47 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=466.627, Time=0.57 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=453.434, Time=1.66 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=464.723, Time=0.75 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=458.732, Time=2.28 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 25.032 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country BE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=816.954, Time=0.29 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=985.545, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=786.931, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=620.294, Time=0.22 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=730.235, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=607.292, Time=0.49 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=658.724, Time=0.14 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=606.499, Time=0.89 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=641.229, Time=0.27 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=608.284, Time=1.55 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=606.990, Time=0.99 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=818.797, Time=0.60 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=608.478, Time=1.27 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=608.469, Time=1.51 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=725.762, Time=0.79 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=603.062, Time=2.99 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=602.698, Time=1.17 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=612.893, Time=0.86 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=659.372, Time=0.70 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=603.439, Time=4.18 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.59 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=605.936, Time=2.02 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=639.575, Time=1.12 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=604.870, Time=3.97 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=609.233, Time=0.60 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=609.251, Time=0.61 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=601.325, Time=1.78 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=608.250, Time=1.45 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=655.569, Time=0.96 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=598.730, Time=3.51 sec ARIMA(2,1,2)(2,1,0)[7] : AIC=635.587, Time=1.34 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=600.821, Time=5.29 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=599.896, Time=4.52 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=601.955, Time=1.55 sec ARIMA(2,1,2)(2,1,1)[7] intercept : AIC=610.256, Time=4.39 sec Best model: ARIMA(2,1,2)(2,1,1)[7] Total fit time: 52.920 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country BE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1048.920, Time=0.19 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1260.599, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=933.680, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=768.988, Time=0.23 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=917.790, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=770.120, Time=0.36 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=770.141, Time=0.44 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=826.155, Time=0.16 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=769.110, Time=1.10 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=1046.928, Time=0.25 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=763.640, Time=0.28 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=912.623, Time=0.23 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=764.835, Time=0.42 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=764.861, Time=0.47 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=818.090, Time=0.20 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=764.336, Time=1.26 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=874.846, Time=0.22 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=765.234, Time=0.61 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=765.989, Time=0.31 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=762.888, Time=0.31 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=913.847, Time=0.13 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=764.136, Time=0.41 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=764.157, Time=0.54 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=818.236, Time=0.20 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=763.602, Time=1.39 sec ARIMA(0,1,2)(0,1,1)[7] intercept : AIC=764.818, Time=1.35 sec Best model: ARIMA(0,1,2)(0,1,1)[7] Total fit time: 11.365 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country BE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-32.224, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=228.105, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-38.152, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-235.367, Time=0.36 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-47.459, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-233.967, Time=1.00 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-233.891, Time=0.86 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-147.156, Time=0.19 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-234.691, Time=1.73 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-32.925, Time=0.20 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-242.252, Time=0.52 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-54.039, Time=0.17 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-241.221, Time=0.72 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-241.085, Time=1.03 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-154.612, Time=0.27 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-240.890, Time=2.02 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-154.824, Time=0.30 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-257.676, Time=0.73 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-69.314, Time=0.15 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-257.853, Time=0.98 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-171.061, Time=0.37 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=2.30 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-256.741, Time=2.64 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-257.456, Time=1.71 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-212.865, Time=0.75 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-255.224, Time=2.84 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-241.128, Time=0.71 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-276.322, Time=1.51 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-278.249, Time=1.94 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-71.998, Time=0.24 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-276.310, Time=3.11 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-178.203, Time=0.55 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-274.432, Time=3.56 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-278.438, Time=0.68 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-60.345, Time=0.21 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-276.683, Time=0.89 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-276.645, Time=1.82 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-176.055, Time=0.41 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-274.827, Time=3.17 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-250.147, Time=0.55 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-276.630, Time=1.68 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 43.519 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country CA Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-8.683, Time=0.37 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=273.722, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-28.181, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-221.241, Time=0.37 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-25.607, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-219.666, Time=0.50 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-219.607, Time=0.84 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-133.681, Time=0.28 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-219.935, Time=1.51 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-9.292, Time=0.28 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-231.476, Time=0.57 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-36.162, Time=0.27 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-230.171, Time=0.71 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-230.072, Time=1.02 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-144.961, Time=0.30 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-229.433, Time=2.09 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-148.997, Time=0.31 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-241.890, Time=0.90 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-46.041, Time=0.16 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-241.517, Time=0.83 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-241.239, Time=1.66 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-156.115, Time=0.34 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-240.068, Time=2.62 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-226.841, Time=0.53 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-266.695, Time=1.54 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-45.151, Time=0.41 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-265.295, Time=1.74 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-265.249, Time=3.02 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-163.353, Time=0.49 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-262.701, Time=3.67 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-268.102, Time=0.76 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-40.865, Time=0.17 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-266.864, Time=1.23 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-266.772, Time=1.60 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-163.875, Time=0.42 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-265.017, Time=3.01 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-239.601, Time=0.60 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-266.917, Time=2.02 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 37.509 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country CA Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-27.349, Time=0.29 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=266.069, Time=0.08 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-44.324, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-248.990, Time=0.28 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-46.303, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-247.295, Time=0.46 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-247.264, Time=0.83 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-155.193, Time=0.29 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-247.957, Time=1.52 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-28.045, Time=0.24 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-260.092, Time=0.54 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-57.287, Time=0.17 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-258.679, Time=0.75 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-258.616, Time=1.19 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-167.283, Time=0.33 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-258.284, Time=2.09 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-174.658, Time=0.36 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-270.884, Time=0.89 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-67.253, Time=0.18 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-270.336, Time=0.98 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-270.135, Time=1.66 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-178.335, Time=0.45 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-269.284, Time=2.57 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-255.372, Time=0.52 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-296.603, Time=1.70 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-66.235, Time=0.26 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-295.159, Time=1.72 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-295.128, Time=3.30 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-185.249, Time=0.48 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-292.603, Time=3.84 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-297.740, Time=0.97 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-61.948, Time=0.19 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-296.499, Time=1.13 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-296.409, Time=1.87 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-185.905, Time=0.50 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-294.650, Time=3.08 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-268.682, Time=0.52 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-296.259, Time=2.01 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 38.552 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country CA Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-18.938, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=287.044, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-39.754, Time=0.23 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-254.405, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-40.858, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-253.016, Time=0.58 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-252.931, Time=0.80 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-156.083, Time=0.26 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-252.798, Time=1.79 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-19.731, Time=0.24 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-266.468, Time=0.56 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-52.310, Time=0.18 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-265.486, Time=0.77 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-265.333, Time=0.90 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-169.100, Time=0.34 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-264.190, Time=2.37 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-175.702, Time=0.36 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-277.624, Time=0.94 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-63.005, Time=0.16 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-277.864, Time=0.96 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-180.375, Time=0.54 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-279.195, Time=2.52 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-227.998, Time=0.78 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-274.048, Time=2.83 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-275.491, Time=2.85 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-266.262, Time=1.74 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-259.245, Time=1.84 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=-301.582, Time=3.30 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-302.952, Time=1.94 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-304.605, Time=1.85 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-61.165, Time=0.32 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-302.923, Time=3.42 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-186.825, Time=0.57 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-300.607, Time=4.22 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-305.274, Time=1.18 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-56.923, Time=0.24 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-303.893, Time=1.33 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-303.809, Time=3.81 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-187.663, Time=0.41 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-302.112, Time=3.72 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-275.399, Time=0.59 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=-303.661, Time=3.15 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 55.405 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country CA Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=42.227, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=337.658, Time=0.08 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-0.962, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-200.702, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-10.490, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-200.975, Time=0.68 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-115.072, Time=0.24 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.14 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-199.961, Time=1.30 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-200.388, Time=0.93 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-166.018, Time=0.50 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-198.162, Time=2.08 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-215.521, Time=0.92 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-214.550, Time=0.55 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-130.483, Time=0.36 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.50 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-213.192, Time=3.36 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-24.865, Time=0.18 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-214.753, Time=1.40 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-178.892, Time=0.95 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-211.917, Time=2.87 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-129.347, Time=0.49 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-223.525, Time=1.15 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-220.589, Time=0.97 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-137.155, Time=0.52 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=2.33 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-219.555, Time=2.87 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-32.245, Time=0.17 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-222.224, Time=2.12 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-183.510, Time=0.78 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-219.610, Time=3.65 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-206.162, Time=1.03 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-254.126, Time=2.75 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-256.419, Time=2.14 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-32.136, Time=0.36 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-254.420, Time=3.47 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-141.778, Time=0.86 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-253.499, Time=4.86 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-255.727, Time=1.25 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=inf, Time=2.60 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 56.527 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country CA Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=677.612, Time=0.29 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=894.134, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=692.732, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=449.514, Time=0.28 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=588.556, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=445.490, Time=0.49 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=545.846, Time=0.18 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=432.014, Time=0.54 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=433.763, Time=0.38 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=425.423, Time=1.07 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=428.289, Time=1.13 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=645.949, Time=0.60 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=423.608, Time=1.22 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=425.786, Time=1.34 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=430.459, Time=0.77 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=443.234, Time=0.64 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=523.578, Time=0.80 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=422.589, Time=1.45 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=423.282, Time=1.76 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=429.912, Time=0.93 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=438.231, Time=0.71 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=475.282, Time=1.03 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=400.832, Time=3.50 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=405.427, Time=2.97 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=409.050, Time=1.69 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=417.273, Time=1.05 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=400.246, Time=2.52 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=404.056, Time=2.25 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=408.592, Time=1.78 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=416.697, Time=1.13 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=422.581, Time=1.99 sec ARIMA(1,1,2)(2,1,2)[7] intercept : AIC=402.280, Time=4.65 sec Best model: ARIMA(1,1,2)(2,1,2)[7] Total fit time: 39.443 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country DE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=707.383, Time=0.29 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=955.721, Time=0.09 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=739.731, Time=0.10 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=479.346, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=638.535, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=473.378, Time=0.43 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=582.724, Time=0.19 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=468.514, Time=0.50 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=470.041, Time=0.30 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=459.993, Time=1.28 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=459.444, Time=1.17 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.60 sec ARIMA(0,1,0)(1,1,2)[7] : AIC=694.968, Time=0.64 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=458.809, Time=1.47 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=0.75 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=472.721, Time=0.57 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=459.757, Time=1.60 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=479.544, Time=0.46 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=468.378, Time=0.78 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=575.834, Time=1.04 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=456.166, Time=1.71 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=0.89 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=467.935, Time=0.64 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=457.688, Time=1.82 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=475.098, Time=0.58 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=467.487, Time=0.75 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=514.114, Time=1.33 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=439.332, Time=5.96 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=2.55 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=450.859, Time=2.58 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=437.936, Time=9.05 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=448.455, Time=2.94 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=438.014, Time=3.26 sec ARIMA(2,1,2)(2,1,2)[7] intercept : AIC=446.441, Time=5.89 sec Best model: ARIMA(2,1,2)(2,1,2)[7] Total fit time: 52.652 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country DE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=725.118, Time=0.20 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=978.868, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=753.858, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=488.419, Time=0.38 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=648.417, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=482.026, Time=0.46 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=590.131, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=471.745, Time=0.49 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=473.025, Time=0.36 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=467.176, Time=1.08 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=467.411, Time=1.08 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=701.158, Time=1.21 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=467.140, Time=1.28 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=466.928, Time=1.32 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=478.038, Time=1.22 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=481.497, Time=0.67 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=488.550, Time=0.42 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=471.692, Time=0.74 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=588.053, Time=1.16 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=464.369, Time=1.98 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=473.943, Time=1.80 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=476.766, Time=0.69 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=465.767, Time=1.80 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=484.045, Time=0.64 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=470.905, Time=0.80 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=525.510, Time=1.28 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=445.706, Time=3.54 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=457.805, Time=2.70 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=458.986, Time=1.49 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=445.149, Time=4.26 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=457.670, Time=1.81 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=445.501, Time=2.79 sec ARIMA(2,1,2)(2,1,2)[7] intercept : AIC=454.430, Time=5.30 sec Best model: ARIMA(2,1,2)(2,1,2)[7] Total fit time: 43.466 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country DE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=738.550, Time=0.21 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1001.088, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=766.022, Time=0.15 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=494.314, Time=0.27 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=659.959, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=486.970, Time=0.44 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=599.391, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=476.640, Time=0.45 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=477.731, Time=0.44 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=471.774, Time=1.12 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=472.238, Time=1.28 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=712.134, Time=0.73 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=471.687, Time=1.27 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=471.860, Time=1.81 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=476.394, Time=0.85 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=486.512, Time=0.75 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=584.581, Time=0.99 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=470.371, Time=1.56 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=469.335, Time=1.62 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=478.776, Time=1.53 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=481.718, Time=0.78 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=489.867, Time=0.51 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=475.436, Time=0.91 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=531.783, Time=1.20 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=449.798, Time=3.32 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=461.737, Time=3.15 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=463.060, Time=1.54 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=449.023, Time=3.30 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=459.738, Time=1.80 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=449.715, Time=2.77 sec ARIMA(2,1,2)(2,1,2)[7] intercept : AIC=458.191, Time=5.49 sec Best model: ARIMA(2,1,2)(2,1,2)[7] Total fit time: 40.641 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country DE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=749.236, Time=0.24 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1022.373, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=777.106, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=496.552, Time=0.32 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=667.242, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=489.507, Time=0.57 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=603.855, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=476.242, Time=0.61 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=477.226, Time=0.37 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=472.188, Time=1.05 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=474.088, Time=1.27 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=720.672, Time=1.23 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=471.863, Time=1.18 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=473.426, Time=1.75 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=475.817, Time=0.80 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=488.846, Time=1.03 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=587.834, Time=0.86 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=470.528, Time=1.43 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=470.599, Time=1.58 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=474.781, Time=0.93 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=483.743, Time=0.77 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=527.820, Time=0.92 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=447.125, Time=3.88 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=448.743, Time=3.39 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=457.873, Time=2.01 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=462.908, Time=1.62 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=447.912, Time=2.80 sec ARIMA(2,1,2)(2,1,2)[7] intercept : AIC=458.269, Time=5.48 sec Best model: ARIMA(2,1,2)(2,1,2)[7] Total fit time: 36.619 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country DE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=660.175, Time=0.20 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=887.800, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=631.373, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=444.239, Time=0.29 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=649.438, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.41 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.89 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=538.783, Time=0.17 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=447.700, Time=0.75 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=658.189, Time=0.16 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=443.220, Time=0.39 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=650.757, Time=0.14 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.94 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.32 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=539.866, Time=0.22 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.60 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=531.959, Time=0.26 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=443.016, Time=0.70 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=652.307, Time=0.20 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.32 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=1.61 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=540.795, Time=0.28 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.48 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=479.049, Time=0.38 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=441.248, Time=1.68 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=653.937, Time=0.37 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=1.06 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=2.69 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=542.665, Time=0.53 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=inf, Time=4.27 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=439.561, Time=0.90 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=652.818, Time=0.15 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=0.91 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=2.23 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=541.221, Time=0.41 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=inf, Time=3.66 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=442.530, Time=0.49 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=inf, Time=2.86 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 40.251 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country DK Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.42 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=913.302, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=659.808, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=448.207, Time=0.38 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=663.439, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.15 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.02 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=559.138, Time=0.21 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.52 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=674.001, Time=0.21 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=446.513, Time=0.50 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=664.509, Time=0.17 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.99 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.35 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=560.383, Time=0.23 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.83 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=539.624, Time=0.34 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=inf, Time=0.80 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=inf, Time=1.51 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=445.662, Time=0.58 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=664.572, Time=0.15 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=inf, Time=1.12 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=inf, Time=1.64 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=560.326, Time=0.34 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=3.92 sec ARIMA(0,1,2)(0,1,1)[7] intercept : AIC=inf, Time=1.23 sec Best model: ARIMA(0,1,2)(0,1,1)[7] Total fit time: 23.905 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country DK Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=941.732, Time=0.08 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=675.185, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=463.331, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=682.582, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.55 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.84 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=572.384, Time=0.18 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.50 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=694.316, Time=0.21 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=460.878, Time=0.51 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=684.269, Time=0.13 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.08 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=0.98 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=573.209, Time=0.20 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.80 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=553.498, Time=0.26 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=459.934, Time=0.76 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=686.052, Time=0.20 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=0.98 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=1.61 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=574.425, Time=0.40 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.60 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=inf, Time=0.39 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=inf, Time=2.21 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=inf, Time=1.71 sec ARIMA(2,1,1)(0,1,1)[7] intercept : AIC=inf, Time=2.09 sec Best model: ARIMA(2,1,1)(0,1,1)[7] Total fit time: 25.226 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country DK Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=965.059, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=687.383, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.41 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=832.479, Time=0.06 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=641.741, Time=0.29 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.05 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.48 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=783.751, Time=0.16 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=581.351, Time=0.40 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=628.804, Time=0.25 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.48 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=0.84 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=545.156, Time=0.53 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=590.611, Time=0.32 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=3.16 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.35 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=546.214, Time=0.43 sec ARIMA(2,1,2)(2,1,0)[7] : AIC=543.899, Time=0.91 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=592.028, Time=0.57 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=inf, Time=3.64 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=1.49 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=542.500, Time=0.81 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=590.633, Time=0.47 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=inf, Time=3.51 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.55 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=545.424, Time=0.40 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=547.323, Time=0.33 sec ARIMA(1,1,2)(2,1,0)[7] intercept : AIC=544.505, Time=3.37 sec Best model: ARIMA(1,1,2)(2,1,0)[7] Total fit time: 29.789 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country DK Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=990.729, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=699.480, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.42 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=850.973, Time=0.13 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=651.722, Time=0.31 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.24 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.58 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=801.751, Time=0.18 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=591.086, Time=0.42 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=640.438, Time=0.22 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=4.80 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=0.73 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=555.887, Time=0.58 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=603.167, Time=0.41 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=3.45 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.14 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=556.596, Time=0.57 sec ARIMA(2,1,2)(2,1,0)[7] : AIC=554.877, Time=1.10 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=604.482, Time=0.59 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=inf, Time=3.61 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=2.49 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=553.411, Time=0.89 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=603.016, Time=0.49 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=inf, Time=3.42 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.61 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=555.790, Time=0.41 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=558.037, Time=0.35 sec ARIMA(1,1,2)(2,1,0)[7] intercept : AIC=555.361, Time=2.92 sec Best model: ARIMA(1,1,2)(2,1,0)[7] Total fit time: 33.617 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country DK Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=292.842, Time=0.28 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=521.447, Time=0.12 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=234.345, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=53.728, Time=0.36 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=253.242, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=54.305, Time=0.44 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=54.459, Time=0.63 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=150.898, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=55.213, Time=2.02 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=292.389, Time=0.18 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=42.971, Time=0.56 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=254.944, Time=0.14 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=44.675, Time=0.69 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=44.705, Time=1.05 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=145.108, Time=0.26 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=46.901, Time=1.02 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=109.276, Time=0.31 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=44.505, Time=0.80 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=44.353, Time=1.04 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=44.259, Time=0.49 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=75.503, Time=0.43 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=46.351, Time=1.17 sec ARIMA(1,1,1)(0,1,1)[7] intercept : AIC=44.173, Time=1.02 sec Best model: ARIMA(1,1,1)(0,1,1)[7] Total fit time: 13.479 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country FI Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=340.872, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=574.878, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=260.270, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=78.181, Time=0.29 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=285.061, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=79.594, Time=0.44 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=79.653, Time=0.70 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=179.594, Time=0.21 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=81.055, Time=2.05 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=339.381, Time=0.21 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=62.418, Time=0.63 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=286.219, Time=0.12 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=64.417, Time=0.74 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=64.417, Time=1.03 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=169.815, Time=0.29 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=65.851, Time=2.37 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=128.792, Time=0.33 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=63.170, Time=0.69 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=62.709, Time=0.97 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=65.009, Time=0.54 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=97.027, Time=0.43 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=60.791, Time=1.88 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=278.653, Time=0.38 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=62.418, Time=1.71 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=62.444, Time=4.01 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=170.977, Time=1.08 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=63.639, Time=4.84 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=77.384, Time=2.63 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 29.167 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country FI Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=359.985, Time=0.30 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=622.529, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=278.469, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=89.281, Time=0.43 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=312.911, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=90.676, Time=0.62 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=90.742, Time=0.92 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=196.544, Time=0.29 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.70 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=358.523, Time=0.24 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=72.979, Time=0.70 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=313.364, Time=0.14 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=74.974, Time=0.89 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=74.974, Time=1.11 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=183.636, Time=0.28 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=76.128, Time=2.56 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=143.657, Time=0.33 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=73.856, Time=1.24 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=73.349, Time=0.96 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=75.548, Time=0.51 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=109.899, Time=0.94 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=71.166, Time=1.85 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=302.673, Time=0.39 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=72.871, Time=1.83 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=72.915, Time=3.63 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=184.213, Time=0.81 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=73.712, Time=3.96 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=78.250, Time=2.26 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 30.249 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country FI Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=395.719, Time=0.36 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=666.802, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=303.058, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=115.374, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=345.037, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=115.098, Time=0.57 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=223.327, Time=0.24 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.04 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.21 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=115.452, Time=1.16 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=185.946, Time=0.45 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=2.97 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=99.000, Time=0.61 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=97.668, Time=0.46 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=344.920, Time=0.17 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=99.092, Time=1.17 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=211.725, Time=0.25 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=99.572, Time=2.96 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=168.976, Time=0.31 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=98.849, Time=0.68 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=98.512, Time=0.94 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=395.048, Time=0.30 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=100.265, Time=0.52 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=131.467, Time=0.41 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=100.455, Time=1.68 sec ARIMA(1,1,1)(0,1,1)[7] intercept : AIC=99.635, Time=1.48 sec Best model: ARIMA(1,1,1)(0,1,1)[7] Total fit time: 21.774 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country FI Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=397.839, Time=0.37 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=676.226, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=300.191, Time=0.26 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=109.081, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=343.614, Time=0.12 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=109.152, Time=0.57 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=109.484, Time=0.91 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=216.601, Time=0.26 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.30 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=397.318, Time=0.35 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=91.221, Time=0.56 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=343.716, Time=0.17 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=92.664, Time=0.69 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=92.750, Time=1.01 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=205.188, Time=0.24 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=95.220, Time=1.14 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=165.800, Time=0.30 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=92.560, Time=0.80 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=92.204, Time=0.88 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=93.581, Time=0.50 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=126.254, Time=0.41 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=94.076, Time=1.70 sec ARIMA(1,1,1)(0,1,1)[7] intercept : AIC=93.195, Time=1.24 sec Best model: ARIMA(1,1,1)(0,1,1)[7] Total fit time: 15.315 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country FI Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1082.913, Time=0.23 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1275.787, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=1023.918, Time=0.11 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=826.676, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=987.792, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=816.406, Time=0.49 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=913.945, Time=0.18 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=818.056, Time=0.77 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=818.077, Time=1.24 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=817.478, Time=0.90 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=883.289, Time=0.33 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=820.055, Time=2.53 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=809.746, Time=0.53 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=819.902, Time=0.35 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=907.876, Time=0.18 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=811.276, Time=1.12 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=811.313, Time=1.51 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=989.485, Time=0.29 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=810.875, Time=0.98 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=876.626, Time=0.39 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=813.275, Time=2.60 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=923.898, Time=0.31 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=808.836, Time=0.74 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=816.439, Time=0.46 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=907.614, Time=0.27 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=810.211, Time=1.20 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=810.312, Time=1.85 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=inf, Time=0.54 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=809.801, Time=1.22 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=876.645, Time=0.43 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=812.211, Time=2.59 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=846.878, Time=0.52 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=810.797, Time=1.12 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=810.534, Time=1.05 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=810.602, Time=2.49 sec Best model: ARIMA(2,1,1)(1,1,1)[7] Total fit time: 29.954 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country FR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1135.057, Time=0.23 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1336.831, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=1068.136, Time=0.11 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=862.925, Time=0.32 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=1028.913, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=852.818, Time=0.50 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=953.158, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=854.452, Time=0.81 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=854.460, Time=1.40 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=853.861, Time=0.63 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=921.211, Time=0.35 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=856.446, Time=2.28 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=845.027, Time=0.54 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=855.449, Time=0.37 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=946.467, Time=0.21 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=846.573, Time=1.04 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=846.589, Time=1.40 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=1030.256, Time=0.15 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=846.148, Time=0.74 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=913.930, Time=0.38 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=848.567, Time=2.52 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=962.946, Time=0.36 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=845.043, Time=0.71 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=846.148, Time=1.01 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=844.150, Time=0.54 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=853.449, Time=0.47 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=945.903, Time=0.19 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=845.609, Time=0.95 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=845.647, Time=1.91 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=1030.482, Time=0.15 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=845.205, Time=0.89 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=913.369, Time=0.36 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=847.605, Time=3.08 sec ARIMA(0,1,2)(1,1,1)[7] intercept : AIC=845.660, Time=1.94 sec Best model: ARIMA(0,1,2)(1,1,1)[7] Total fit time: 26.891 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country FR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1167.415, Time=0.22 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1386.221, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=1101.005, Time=0.12 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=883.831, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=1061.842, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=872.894, Time=0.44 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=981.235, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=874.451, Time=0.81 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=874.447, Time=1.27 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=874.053, Time=0.75 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=946.600, Time=0.37 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=876.438, Time=2.73 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=864.439, Time=0.52 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=875.812, Time=0.37 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=974.593, Time=0.21 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=865.919, Time=1.18 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=865.924, Time=1.56 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=1063.042, Time=0.16 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=865.681, Time=0.78 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=939.165, Time=0.44 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=867.907, Time=2.99 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=987.368, Time=0.38 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=864.419, Time=0.77 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=873.562, Time=0.55 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=975.639, Time=0.32 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=865.786, Time=1.27 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=865.828, Time=1.78 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=1051.160, Time=0.26 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=865.512, Time=1.04 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=940.121, Time=0.47 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=867.781, Time=2.70 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=906.687, Time=0.49 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=866.349, Time=1.29 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=865.496, Time=0.97 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=865.679, Time=2.54 sec Best model: ARIMA(2,1,1)(1,1,1)[7] Total fit time: 30.417 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country FR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1204.503, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1431.136, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=1132.738, Time=0.13 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=912.484, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=1096.173, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=900.193, Time=0.51 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=1010.836, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=901.519, Time=0.93 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=901.537, Time=1.24 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=901.696, Time=0.72 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=976.382, Time=0.35 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=903.508, Time=2.37 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=890.987, Time=0.57 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=903.934, Time=0.37 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=1002.699, Time=0.21 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=892.201, Time=1.39 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=892.229, Time=1.52 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=1096.001, Time=0.14 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=892.611, Time=0.81 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=967.608, Time=0.40 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=894.189, Time=2.98 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=1018.014, Time=0.40 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=890.277, Time=0.76 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=900.633, Time=0.53 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=1003.208, Time=0.29 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=891.369, Time=1.24 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=891.455, Time=1.89 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=inf, Time=0.31 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=891.664, Time=1.02 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=967.965, Time=0.53 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=893.366, Time=3.34 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=933.133, Time=0.56 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=892.228, Time=1.29 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=891.690, Time=1.02 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=892.107, Time=2.53 sec Best model: ARIMA(2,1,1)(1,1,1)[7] Total fit time: 31.316 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country FR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=1234.572, Time=0.28 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=1475.020, Time=0.12 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=1163.559, Time=0.14 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=938.466, Time=0.30 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=1133.278, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=925.300, Time=0.54 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=1041.233, Time=0.19 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=926.322, Time=0.93 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=926.350, Time=1.42 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=927.091, Time=0.86 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=1005.035, Time=0.36 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=928.934, Time=1.24 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=914.949, Time=0.63 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=928.962, Time=0.37 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=1032.365, Time=0.22 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=915.903, Time=1.33 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=915.943, Time=1.63 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=1132.212, Time=0.13 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=916.853, Time=0.86 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=995.579, Time=0.39 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=917.885, Time=2.99 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=1040.951, Time=0.38 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=913.804, Time=0.70 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=925.269, Time=0.57 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=1032.520, Time=0.30 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=914.659, Time=1.44 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=914.767, Time=2.17 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=1122.792, Time=0.26 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=915.429, Time=1.12 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=995.633, Time=0.50 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=916.654, Time=3.41 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=954.150, Time=0.62 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=915.788, Time=1.54 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=915.326, Time=1.04 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=915.802, Time=2.32 sec Best model: ARIMA(2,1,1)(1,1,1)[7] Total fit time: 31.397 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country FR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-458.761, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-282.569, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-410.417, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-487.305, Time=0.27 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-326.554, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-490.410, Time=0.48 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-424.096, Time=0.21 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-492.360, Time=1.31 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-439.535, Time=0.35 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-491.365, Time=2.24 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.86 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=-458.041, Time=0.69 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=1.99 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=1.60 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-481.649, Time=1.12 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=inf, Time=3.29 sec ARIMA(0,1,1)(2,1,1)[7] intercept : AIC=inf, Time=2.44 sec Best model: ARIMA(0,1,1)(2,1,1)[7] Total fit time: 18.490 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country GB Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-492.757, Time=0.31 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-310.831, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-444.089, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-519.378, Time=0.27 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-357.052, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-524.193, Time=0.60 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-458.097, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.30 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.34 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-522.328, Time=0.76 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-472.830, Time=0.36 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-526.829, Time=2.29 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=-492.834, Time=1.89 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-528.876, Time=3.18 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.32 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.67 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-526.184, Time=0.94 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-516.719, Time=2.36 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-528.205, Time=3.63 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-527.573, Time=4.30 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=-529.572, Time=3.55 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=3.21 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=1.72 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-527.237, Time=0.84 sec ARIMA(0,1,2)(2,1,2)[7] intercept : AIC=-526.777, Time=4.13 sec Best model: ARIMA(0,1,2)(2,1,2)[7] Total fit time: 43.524 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country GB Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-529.643, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-338.977, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-479.184, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-556.777, Time=0.40 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-386.498, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-561.223, Time=0.58 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-493.389, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.11 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-559.335, Time=0.73 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-508.675, Time=0.29 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-565.112, Time=1.82 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=-530.725, Time=2.05 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=inf, Time=3.22 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=inf, Time=3.73 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-555.073, Time=2.86 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=inf, Time=4.00 sec ARIMA(0,1,1)(2,1,2)[7] intercept : AIC=-562.372, Time=3.26 sec Best model: ARIMA(0,1,1)(2,1,2)[7] Total fit time: 27.166 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country GB Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-560.681, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-359.597, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-508.854, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-591.527, Time=0.29 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-412.708, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-596.231, Time=0.49 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-523.246, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.53 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.10 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-594.454, Time=0.94 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-540.231, Time=0.40 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-599.312, Time=2.44 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=-561.122, Time=1.99 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-600.221, Time=3.05 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.26 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.32 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-597.253, Time=1.17 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-589.459, Time=2.86 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-599.089, Time=3.83 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-598.475, Time=4.40 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=-600.627, Time=3.71 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=2.75 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=2.14 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-597.956, Time=0.85 sec ARIMA(0,1,2)(2,1,2)[7] intercept : AIC=-597.719, Time=4.41 sec Best model: ARIMA(0,1,2)(2,1,2)[7] Total fit time: 44.847 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country GB Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-587.923, Time=0.40 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-378.835, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-530.238, Time=0.22 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-612.923, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-425.492, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-619.879, Time=0.50 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-541.015, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.63 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.21 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-617.254, Time=0.98 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-558.667, Time=0.42 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=2.55 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-620.324, Time=0.81 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-612.260, Time=0.61 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-541.121, Time=0.48 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.58 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.92 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-433.305, Time=0.19 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-617.319, Time=1.14 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-558.287, Time=0.96 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=inf, Time=3.33 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-612.046, Time=0.62 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-619.793, Time=1.25 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-619.126, Time=1.49 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-621.034, Time=0.82 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-568.998, Time=0.16 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=-541.023, Time=0.26 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=1.77 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=2.72 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=-433.023, Time=0.16 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-617.876, Time=2.60 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-558.357, Time=0.52 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=inf, Time=4.53 sec ARIMA(0,1,2)(1,1,1)[7] intercept : AIC=-619.052, Time=2.25 sec Best model: ARIMA(0,1,2)(1,1,1)[7] Total fit time: 41.806 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country GB Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-950.080, Time=0.37 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-726.311, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-923.473, Time=0.26 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1048.220, Time=0.62 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-842.118, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1046.314, Time=0.65 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1046.301, Time=1.02 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-959.067, Time=0.24 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1046.284, Time=1.63 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-952.008, Time=0.22 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1046.995, Time=0.66 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1047.164, Time=0.81 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1014.766, Time=0.42 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1045.426, Time=1.17 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1046.875, Time=0.96 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.172 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country ID Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-989.642, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-742.958, Time=0.11 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-937.267, Time=0.53 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1072.391, Time=0.56 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-828.298, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1070.431, Time=0.65 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1070.428, Time=1.18 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-963.814, Time=0.25 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1070.331, Time=2.02 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-991.642, Time=0.36 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1074.271, Time=0.89 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-849.798, Time=0.28 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1072.296, Time=0.93 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1072.293, Time=1.31 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-966.446, Time=0.47 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-1072.699, Time=2.52 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1044.588, Time=0.28 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-1072.275, Time=1.56 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1072.281, Time=1.43 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1074.235, Time=0.90 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-1064.657, Time=0.66 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-1071.592, Time=1.78 sec ARIMA(1,1,1)(0,1,1)[7] intercept : AIC=-1072.318, Time=1.47 sec Best model: ARIMA(1,1,1)(0,1,1)[7] Total fit time: 20.605 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country ID Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1022.540, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-766.100, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-976.611, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1099.528, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-857.993, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1097.529, Time=0.74 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1097.529, Time=0.88 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1002.600, Time=0.28 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1098.905, Time=1.83 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1024.538, Time=0.26 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1098.769, Time=0.90 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1098.990, Time=0.73 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1077.195, Time=0.41 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1097.130, Time=0.91 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1097.425, Time=0.84 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.002 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country ID Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1075.414, Time=0.42 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-811.142, Time=0.09 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1021.250, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1146.273, Time=0.42 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-904.928, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1144.289, Time=0.62 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1144.287, Time=1.04 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1047.130, Time=0.26 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1145.778, Time=2.23 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1077.360, Time=0.27 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1145.463, Time=0.45 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1145.643, Time=0.69 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1126.990, Time=0.89 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1143.750, Time=1.05 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1146.050, Time=1.15 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.977 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country ID Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.58 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-806.503, Time=0.09 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1009.102, Time=0.33 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1101.511, Time=0.41 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-881.195, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1100.434, Time=0.61 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1100.078, Time=0.84 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1027.800, Time=0.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1099.613, Time=1.76 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1037.112, Time=0.26 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1101.261, Time=0.70 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1101.490, Time=0.64 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1084.380, Time=0.47 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1099.579, Time=1.47 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1099.552, Time=0.94 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.432 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country ID Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.47 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=443.553, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=240.946, Time=0.15 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=109.181, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=308.014, Time=0.06 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.27 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=2.27 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=203.417, Time=0.19 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.40 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=223.296, Time=0.20 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=107.886, Time=0.65 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=309.614, Time=0.11 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.33 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=2.14 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=204.583, Time=0.21 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.60 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=137.950, Time=0.31 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=97.506, Time=0.85 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=305.861, Time=0.15 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.39 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=2.15 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=199.871, Time=0.33 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.19 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=96.177, Time=0.48 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=307.910, Time=0.09 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.45 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=inf, Time=1.74 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=200.767, Time=0.26 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=2.75 sec ARIMA(2,1,0)(0,1,1)[7] intercept : AIC=inf, Time=0.87 sec Best model: ARIMA(2,1,0)(0,1,1)[7] Total fit time: 31.466 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country IE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.39 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=449.327, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=233.148, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=95.217, Time=0.39 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=305.433, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.35 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.59 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=194.107, Time=0.19 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.57 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=215.538, Time=0.21 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=93.663, Time=0.57 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=306.916, Time=0.11 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.28 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=2.10 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=195.239, Time=0.25 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.81 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=125.057, Time=0.32 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=83.194, Time=0.77 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=303.465, Time=0.15 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.00 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=1.95 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=190.570, Time=0.34 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.09 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=81.933, Time=0.46 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=305.988, Time=0.09 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.76 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=inf, Time=1.67 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=191.648, Time=0.19 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=3.14 sec ARIMA(2,1,0)(0,1,1)[7] intercept : AIC=inf, Time=0.76 sec Best model: ARIMA(2,1,0)(0,1,1)[7] Total fit time: 30.816 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country IE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.41 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=463.940, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=236.864, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=90.315, Time=0.42 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=310.803, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.05 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.09 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=194.808, Time=0.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.38 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=218.039, Time=0.23 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=88.655, Time=0.83 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=312.241, Time=0.22 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.21 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.51 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=195.744, Time=0.26 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.75 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=122.458, Time=0.35 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=inf, Time=0.82 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=inf, Time=1.92 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=inf, Time=0.59 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=inf, Time=0.49 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=73.850, Time=1.25 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=254.530, Time=0.35 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=1.50 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=2.51 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=190.463, Time=0.51 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=inf, Time=4.19 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=75.410, Time=2.23 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 29.609 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country IE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.51 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=487.632, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=240.528, Time=0.36 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=88.344, Time=0.64 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=323.378, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.08 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.09 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=196.054, Time=0.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.69 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=221.938, Time=0.26 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=86.249, Time=0.69 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=324.489, Time=0.12 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.12 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.74 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=196.752, Time=0.25 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=3.28 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=121.001, Time=0.38 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=74.504, Time=0.76 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=319.292, Time=0.16 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.62 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=1.77 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=190.678, Time=0.37 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.30 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=73.036, Time=0.51 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=321.081, Time=0.09 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=0.96 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=inf, Time=1.20 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=191.557, Time=0.24 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=3.33 sec ARIMA(2,1,0)(0,1,1)[7] intercept : AIC=74.959, Time=0.99 sec Best model: ARIMA(2,1,0)(0,1,1)[7] Total fit time: 29.878 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country IE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.45 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=489.876, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=235.137, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.44 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=375.147, Time=0.10 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=180.214, Time=0.38 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.87 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.69 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=284.928, Time=0.19 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=135.800, Time=0.64 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=184.989, Time=0.30 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.62 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=0.98 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=136.440, Time=0.59 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=143.189, Time=0.68 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=137.792, Time=1.19 sec Best model: ARIMA(2,1,0)(2,1,0)[7] Total fit time: 12.334 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country IE Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=788.757, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=568.264, Time=0.13 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=391.596, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=549.097, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.52 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=380.492, Time=0.82 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=379.996, Time=1.01 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=379.550, Time=1.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=0.73 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=inf, Time=1.04 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=377.965, Time=1.71 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=378.310, Time=1.37 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=380.505, Time=1.30 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=378.505, Time=0.61 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=440.182, Time=1.39 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=377.184, Time=2.26 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=377.578, Time=1.75 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=379.594, Time=1.42 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=377.594, Time=0.78 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=397.509, Time=1.39 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=361.743, Time=4.42 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=359.772, Time=3.97 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=362.199, Time=3.24 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=362.351, Time=1.85 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=363.594, Time=1.29 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=364.272, Time=3.26 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=358.391, Time=3.30 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=361.192, Time=2.49 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=361.585, Time=1.41 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=360.341, Time=4.43 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=364.239, Time=1.04 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=363.220, Time=3.01 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=377.191, Time=1.48 sec ARIMA(1,1,2)(1,1,2)[7] intercept : AIC=364.501, Time=4.39 sec Best model: ARIMA(1,1,2)(1,1,2)[7] Total fit time: 59.748 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country IL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=807.708, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=577.512, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=399.277, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=556.786, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.57 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.78 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=491.779, Time=0.19 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=384.395, Time=1.07 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=1.09 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=0.90 sec ARIMA(0,1,0)(1,1,2)[7] : AIC=inf, Time=0.74 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=383.121, Time=1.74 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=382.982, Time=1.12 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=398.316, Time=0.45 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.62 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=inf, Time=0.88 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=382.313, Time=1.24 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=397.318, Time=0.70 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=382.608, Time=1.98 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=0.82 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=405.070, Time=1.00 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=3.33 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=2.44 sec ARIMA(2,1,1)(0,1,2)[7] intercept : AIC=inf, Time=3.00 sec Best model: ARIMA(2,1,1)(0,1,2)[7] Total fit time: 25.643 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country IL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.75 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=826.057, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=586.473, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=408.124, Time=0.30 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=569.120, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.68 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.97 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=500.227, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=394.289, Time=1.30 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=1.57 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.03 sec ARIMA(0,1,0)(1,1,2)[7] : AIC=inf, Time=1.14 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=393.148, Time=1.58 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.04 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.77 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=inf, Time=1.99 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=407.047, Time=0.42 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=1.71 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=455.014, Time=1.36 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=392.756, Time=1.86 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=392.366, Time=1.35 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=405.975, Time=0.62 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=0.88 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=414.474, Time=1.05 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=3.66 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=inf, Time=0.94 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=2.69 sec ARIMA(2,1,1)(0,1,2)[7] intercept : AIC=inf, Time=3.41 sec Best model: ARIMA(2,1,1)(0,1,2)[7] Total fit time: 33.600 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country IL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.79 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=858.776, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=609.278, Time=0.26 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=425.979, Time=0.33 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=589.214, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.85 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.94 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=518.159, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=413.253, Time=1.22 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=1.79 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.96 sec ARIMA(0,1,0)(1,1,2)[7] : AIC=inf, Time=1.23 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=411.451, Time=1.76 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=410.857, Time=1.05 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=424.147, Time=0.41 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.88 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=inf, Time=0.90 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=410.019, Time=1.70 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=422.811, Time=0.56 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=410.522, Time=2.10 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.08 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=432.442, Time=1.12 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=3.85 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=3.46 sec ARIMA(2,1,1)(0,1,2)[7] intercept : AIC=411.998, Time=3.50 sec Best model: ARIMA(2,1,1)(0,1,2)[7] Total fit time: 32.127 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country IL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.41 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=887.545, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=621.625, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=428.003, Time=0.37 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=605.498, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.81 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=417.120, Time=0.90 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=417.351, Time=1.20 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=inf, Time=0.78 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=414.606, Time=1.05 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=425.743, Time=0.44 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=414.901, Time=1.54 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=0.89 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=485.462, Time=0.79 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=413.320, Time=1.28 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=424.282, Time=0.50 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=413.572, Time=2.05 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=0.78 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=435.060, Time=1.11 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=392.917, Time=3.88 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=395.192, Time=1.56 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=391.127, Time=4.61 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=2.32 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=inf, Time=5.28 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=inf, Time=3.60 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=389.505, Time=4.17 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=391.709, Time=3.89 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.67 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=inf, Time=5.02 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=395.620, Time=1.01 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=inf, Time=2.82 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=413.554, Time=1.86 sec ARIMA(1,1,2)(1,1,2)[7] intercept : AIC=inf, Time=4.57 sec Best model: ARIMA(1,1,2)(1,1,2)[7] Total fit time: 61.531 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country IL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-552.685, Time=0.36 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-135.604, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-522.236, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-682.402, Time=0.79 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-447.525, Time=0.12 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-694.178, Time=0.54 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-592.017, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-693.041, Time=0.63 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-692.866, Time=1.33 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-694.834, Time=1.01 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-561.854, Time=0.58 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-710.502, Time=1.11 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-702.879, Time=0.54 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-708.524, Time=1.74 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-710.245, Time=0.57 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-681.526, Time=1.34 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-712.743, Time=1.10 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-706.343, Time=0.88 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-710.763, Time=2.39 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-712.543, Time=1.21 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-712.127, Time=1.39 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-772.302, Time=3.24 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-762.906, Time=1.76 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-760.086, Time=3.23 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-777.846, Time=2.03 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-640.438, Time=1.01 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=-743.700, Time=2.79 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-492.071, Time=0.41 sec ARIMA(2,1,2)(2,1,0)[7] : AIC=-698.590, Time=1.81 sec ARIMA(2,1,2)(2,1,2)[7] : AIC=-776.805, Time=3.70 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-781.348, Time=1.64 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=inf, Time=1.39 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-642.193, Time=0.61 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-782.712, Time=2.98 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-701.036, Time=1.37 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-780.489, Time=3.68 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-781.743, Time=2.99 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=-715.023, Time=1.05 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-708.567, Time=1.17 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-710.811, Time=1.96 sec ARIMA(1,1,2)(2,1,1)[7] intercept : AIC=-775.020, Time=4.04 sec Best model: ARIMA(1,1,2)(2,1,1)[7] Total fit time: 60.979 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country IN Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-592.999, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-162.965, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-567.262, Time=0.25 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-705.753, Time=0.55 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-482.558, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-711.783, Time=0.71 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-632.325, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-710.160, Time=1.22 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-709.803, Time=1.29 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-710.802, Time=0.84 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-683.160, Time=0.40 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-707.924, Time=2.23 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-730.677, Time=0.96 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-726.578, Time=0.55 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-659.071, Time=0.32 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-729.232, Time=2.26 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-728.717, Time=2.09 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-517.868, Time=0.16 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-730.019, Time=1.63 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-702.506, Time=1.19 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-726.687, Time=1.68 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-712.829, Time=0.78 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-734.438, Time=1.23 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-730.867, Time=1.05 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-663.988, Time=0.59 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-732.728, Time=2.20 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-732.474, Time=2.42 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-525.222, Time=0.20 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-733.864, Time=1.97 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-706.789, Time=1.13 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-730.453, Time=1.65 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-736.259, Time=0.88 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-732.432, Time=0.33 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-637.455, Time=0.78 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-734.445, Time=1.82 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-734.295, Time=1.52 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-471.887, Time=0.15 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-735.676, Time=1.11 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-695.665, Time=0.53 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-732.275, Time=1.95 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-734.537, Time=1.91 sec Best model: ARIMA(2,1,0)(1,1,1)[7] Total fit time: 43.256 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country IN Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-637.569, Time=0.45 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-191.293, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-613.971, Time=0.28 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-748.918, Time=0.46 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-524.106, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-759.851, Time=0.57 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-680.385, Time=0.26 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-758.816, Time=0.65 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-758.362, Time=0.87 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-760.118, Time=0.95 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-641.356, Time=1.22 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-780.622, Time=1.61 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-772.849, Time=0.54 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-778.789, Time=1.83 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-780.583, Time=0.79 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-760.080, Time=1.85 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-784.600, Time=1.73 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-777.910, Time=0.92 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-782.758, Time=2.30 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-784.604, Time=0.74 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-713.272, Time=0.61 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-782.898, Time=1.49 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-568.480, Time=0.22 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-758.005, Time=0.89 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-780.956, Time=2.65 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-786.100, Time=0.80 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-779.243, Time=0.33 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-686.529, Time=0.39 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-784.399, Time=0.95 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-784.257, Time=1.33 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-514.008, Time=0.14 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-786.094, Time=1.76 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-747.006, Time=0.81 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-782.458, Time=2.50 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-760.135, Time=0.56 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-784.936, Time=1.80 sec Best model: ARIMA(2,1,0)(1,1,1)[7] Total fit time: 35.412 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country IN Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-685.572, Time=0.49 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-220.973, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-661.157, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.31 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.37 sec ARIMA(0,1,0)(1,1,0)[7] : AIC=-455.006, Time=0.15 sec ARIMA(0,1,0)(2,1,1)[7] : AIC=-688.540, Time=0.76 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-565.826, Time=0.51 sec ARIMA(0,1,0)(2,1,2)[7] : AIC=-686.573, Time=2.52 sec ARIMA(0,1,0)(1,1,2)[7] : AIC=-687.472, Time=1.54 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=-811.356, Time=2.03 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-813.199, Time=0.53 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-801.365, Time=0.32 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=-811.286, Time=1.79 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-453.834, Time=0.09 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-812.747, Time=1.08 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-738.421, Time=0.63 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-809.446, Time=2.78 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-839.071, Time=0.94 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-833.720, Time=0.35 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-735.985, Time=0.46 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=-837.094, Time=0.95 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-837.079, Time=1.59 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-557.401, Time=0.16 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-838.471, Time=1.82 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-797.270, Time=0.53 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-835.117, Time=1.49 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-837.267, Time=1.07 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-832.812, Time=0.59 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-837.461, Time=1.82 sec Best model: ARIMA(2,1,0)(1,1,1)[7] Total fit time: 27.936 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country IN Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-425.855, Time=0.40 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-18.105, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-459.068, Time=0.25 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-622.391, Time=0.77 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-389.181, Time=0.22 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.72 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-625.548, Time=1.55 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-622.837, Time=2.61 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-427.899, Time=0.52 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-649.615, Time=1.23 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-648.467, Time=0.62 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-647.696, Time=2.62 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-649.682, Time=0.84 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-571.989, Time=0.37 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-647.948, Time=1.08 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-422.279, Time=0.20 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-627.280, Time=0.62 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-646.080, Time=2.13 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-598.684, Time=0.68 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-655.798, Time=1.15 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-655.098, Time=1.08 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-577.099, Time=0.61 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=-653.852, Time=2.20 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=-653.796, Time=2.99 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-427.083, Time=0.22 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-655.685, Time=1.13 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-633.250, Time=0.99 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=-652.082, Time=2.57 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-650.876, Time=0.88 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-743.611, Time=2.00 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-736.751, Time=1.90 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-589.836, Time=1.11 sec ARIMA(2,1,2)(2,1,1)[7] : AIC=inf, Time=3.16 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-738.962, Time=4.11 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-426.738, Time=0.35 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-743.811, Time=3.54 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-739.732, Time=2.61 sec ARIMA(2,1,2)(0,1,2)[7] intercept : AIC=-649.863, Time=4.37 sec Best model: ARIMA(2,1,2)(0,1,2)[7] Total fit time: 55.484 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country IN Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-494.009, Time=0.36 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-305.836, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-438.934, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-536.044, Time=0.27 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-414.835, Time=0.12 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-550.191, Time=0.52 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-462.738, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-548.821, Time=1.05 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-549.193, Time=1.42 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-551.190, Time=1.11 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-495.572, Time=0.78 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-549.426, Time=1.64 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-549.476, Time=1.93 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-543.588, Time=1.07 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-551.676, Time=3.01 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-532.542, Time=1.34 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-549.573, Time=3.21 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-548.993, Time=1.85 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-549.317, Time=3.38 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-547.795, Time=2.07 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-546.691, Time=3.37 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 28.971 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country IT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-526.158, Time=0.31 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-333.286, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-471.966, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-571.346, Time=0.24 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-448.571, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-585.664, Time=0.48 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-497.385, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-584.215, Time=0.99 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-584.637, Time=1.54 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-586.636, Time=1.11 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-527.757, Time=0.80 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-584.925, Time=1.43 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-584.989, Time=1.86 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-578.730, Time=1.53 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-586.915, Time=3.13 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-567.427, Time=0.50 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-582.925, Time=3.42 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-584.494, Time=2.02 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-583.037, Time=3.90 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-583.348, Time=1.87 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-582.921, Time=3.57 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 29.242 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country IT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-527.834, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-336.013, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-486.601, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-586.927, Time=0.23 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-463.887, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-598.006, Time=0.66 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-514.348, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-596.651, Time=1.14 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-597.702, Time=1.35 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-599.434, Time=1.19 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-529.469, Time=0.81 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-597.846, Time=1.83 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-597.927, Time=1.64 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-589.456, Time=1.70 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-599.603, Time=3.01 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-583.661, Time=1.11 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-598.560, Time=3.13 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-596.661, Time=1.80 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-595.416, Time=3.27 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-596.239, Time=1.22 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-598.336, Time=3.63 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 28.627 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country IT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-558.552, Time=0.33 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-337.617, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-499.038, Time=0.23 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-606.144, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-471.051, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-622.216, Time=0.65 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-525.648, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-620.453, Time=1.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-621.275, Time=1.52 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-623.221, Time=1.65 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-560.226, Time=0.82 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-621.671, Time=1.49 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-621.758, Time=2.70 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-615.751, Time=1.16 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-623.999, Time=3.28 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-602.392, Time=0.59 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-619.111, Time=3.44 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-621.232, Time=1.91 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-617.684, Time=3.64 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-619.961, Time=2.44 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-617.205, Time=3.67 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 31.494 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country IT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-596.920, Time=0.32 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-368.964, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-535.353, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-643.053, Time=0.37 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-503.382, Time=0.17 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-660.880, Time=0.84 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-560.378, Time=0.33 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-658.918, Time=1.12 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-659.282, Time=1.66 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-661.282, Time=2.00 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-598.512, Time=0.98 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-659.866, Time=1.76 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-659.982, Time=2.13 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-654.686, Time=1.28 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-662.487, Time=3.48 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-639.940, Time=1.11 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-658.080, Time=3.49 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-660.281, Time=1.77 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-659.666, Time=3.88 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-658.150, Time=2.84 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-656.608, Time=3.81 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 33.598 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country IT Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-828.431, Time=0.31 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-611.747, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-791.236, Time=0.30 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-888.226, Time=0.40 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-725.913, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-894.490, Time=0.61 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-803.109, Time=0.23 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-892.491, Time=1.25 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-892.495, Time=1.68 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-894.462, Time=1.15 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-847.063, Time=0.50 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-890.492, Time=1.21 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-892.620, Time=1.19 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-892.564, Time=0.79 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-887.672, Time=0.54 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-893.980, Time=1.60 sec ARIMA(0,1,1)(1,1,1)[7] intercept : AIC=-892.664, Time=1.47 sec Best model: ARIMA(0,1,1)(1,1,1)[7] Total fit time: 13.352 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country JP Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-883.652, Time=0.37 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-658.261, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-834.109, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-937.947, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-764.591, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-945.695, Time=0.46 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-841.169, Time=0.25 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-943.786, Time=1.35 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-943.852, Time=1.59 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-945.846, Time=1.08 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-884.016, Time=0.79 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-943.922, Time=1.84 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-943.888, Time=1.69 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-942.348, Time=1.17 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-946.321, Time=3.57 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-937.094, Time=0.99 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-944.307, Time=3.02 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-946.123, Time=1.49 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-946.511, Time=3.56 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-936.911, Time=1.55 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-944.534, Time=3.79 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-946.409, Time=1.77 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-944.020, Time=2.16 sec ARIMA(2,1,2)(0,1,2)[7] intercept : AIC=-942.241, Time=3.99 sec Best model: ARIMA(2,1,2)(0,1,2)[7] Total fit time: 37.141 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country JP Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-939.891, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-706.299, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-889.007, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-996.143, Time=0.49 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-816.543, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1005.212, Time=0.69 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-895.409, Time=0.44 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-1003.245, Time=2.13 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1003.276, Time=1.80 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1005.223, Time=1.08 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-940.295, Time=0.86 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1003.424, Time=1.54 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-1003.335, Time=2.11 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1002.114, Time=1.02 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-1006.117, Time=2.75 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-995.662, Time=1.06 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-1004.189, Time=3.26 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-1006.084, Time=1.64 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-1006.063, Time=3.36 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=-1003.503, Time=1.36 sec ARIMA(1,1,2)(0,1,2)[7] intercept : AIC=-1003.950, Time=3.69 sec Best model: ARIMA(1,1,2)(0,1,2)[7] Total fit time: 29.989 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country JP Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-996.336, Time=0.36 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-754.995, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-944.738, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1051.300, Time=0.44 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-869.384, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1062.195, Time=1.14 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-950.623, Time=0.27 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-1060.197, Time=1.41 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1060.198, Time=1.72 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1061.989, Time=1.18 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-996.868, Time=0.67 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1058.206, Time=1.56 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1060.641, Time=1.06 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-1060.440, Time=1.13 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1059.993, Time=0.58 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-1063.481, Time=1.68 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1051.209, Time=0.98 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-953.252, Time=0.61 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-1061.539, Time=2.64 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-1061.644, Time=3.46 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-875.994, Time=0.24 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-1063.413, Time=3.09 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-998.025, Time=1.59 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-1059.627, Time=3.47 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-1063.371, Time=1.88 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-1060.715, Time=1.77 sec ARIMA(1,1,2)(1,1,1)[7] intercept : AIC=-1061.365, Time=2.42 sec Best model: ARIMA(1,1,2)(1,1,1)[7] Total fit time: 35.700 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country JP Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1021.342, Time=0.43 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-766.772, Time=0.07 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-956.623, Time=0.24 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1064.025, Time=0.51 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-864.884, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1072.118, Time=0.78 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-962.733, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-1070.191, Time=1.08 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1070.331, Time=2.31 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1071.731, Time=1.33 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-1010.271, Time=0.56 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1068.388, Time=2.64 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1070.733, Time=1.54 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-1070.474, Time=0.79 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1071.691, Time=0.66 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-1073.116, Time=1.72 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1063.947, Time=1.30 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-964.023, Time=0.68 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-1071.152, Time=2.85 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-1071.077, Time=3.43 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-870.025, Time=0.33 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-1072.689, Time=2.80 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-1010.064, Time=1.55 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-1069.253, Time=3.95 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-1072.261, Time=1.96 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-1069.824, Time=1.63 sec ARIMA(1,1,2)(1,1,1)[7] intercept : AIC=-1070.832, Time=2.43 sec Best model: ARIMA(1,1,2)(1,1,1)[7] Total fit time: 37.923 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country JP Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1095.089, Time=0.39 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-796.912, Time=0.11 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1003.073, Time=0.24 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1125.972, Time=0.49 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-867.617, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1124.556, Time=0.70 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1124.560, Time=1.31 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1005.448, Time=0.33 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1122.627, Time=1.21 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1092.720, Time=0.41 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1124.148, Time=1.09 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1124.305, Time=0.83 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1122.714, Time=0.50 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1122.730, Time=1.25 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1123.978, Time=0.94 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.883 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country KR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1158.263, Time=0.39 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-843.040, Time=0.09 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1060.021, Time=0.25 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1190.015, Time=0.61 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-915.318, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1188.907, Time=0.65 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1188.913, Time=1.23 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1062.330, Time=0.24 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1187.787, Time=2.23 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1155.309, Time=0.28 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1188.250, Time=0.86 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1188.455, Time=0.67 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1100.701, Time=0.11 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1186.705, Time=1.33 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1188.019, Time=1.28 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 10.295 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country KR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1223.626, Time=0.71 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-897.126, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1121.172, Time=0.45 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1256.077, Time=0.56 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-970.699, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1255.100, Time=0.64 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1255.119, Time=2.07 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1123.330, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1252.957, Time=1.11 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1220.363, Time=0.47 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1254.340, Time=1.10 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1254.562, Time=1.22 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1253.170, Time=0.36 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1252.757, Time=1.26 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1254.100, Time=0.94 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 11.227 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country KR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1283.823, Time=0.39 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-948.463, Time=0.07 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1182.017, Time=0.29 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1314.764, Time=0.55 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1021.999, Time=0.16 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1313.658, Time=1.48 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1313.654, Time=1.20 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1183.867, Time=0.32 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1312.370, Time=2.34 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1280.865, Time=0.23 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1313.150, Time=1.22 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1313.522, Time=0.81 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1312.625, Time=0.36 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1311.392, Time=1.36 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1312.861, Time=1.25 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 12.054 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country KR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1347.488, Time=0.40 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-999.701, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1244.347, Time=0.22 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1380.139, Time=0.52 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1077.257, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1379.221, Time=0.66 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1379.206, Time=1.03 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1245.736, Time=0.35 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-1377.407, Time=1.10 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-1343.951, Time=0.34 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1378.615, Time=0.96 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-1379.075, Time=0.69 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1378.020, Time=0.39 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-1376.658, Time=1.57 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-1378.206, Time=0.85 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 9.212 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country KR Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=165.888, Time=0.23 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=395.790, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=140.539, Time=0.19 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-17.320, Time=0.31 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=207.424, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-15.366, Time=0.49 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-15.367, Time=0.85 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=94.090, Time=0.24 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-13.323, Time=0.71 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=163.947, Time=0.19 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-15.642, Time=0.53 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-15.546, Time=0.53 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=34.204, Time=0.26 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-15.692, Time=0.94 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-15.886, Time=0.87 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 6.526 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country MX Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=165.762, Time=0.24 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=403.599, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=137.699, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-24.987, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=206.972, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-23.017, Time=0.72 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-23.017, Time=0.73 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=87.264, Time=0.23 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-21.005, Time=0.74 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=163.799, Time=0.19 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-23.429, Time=0.51 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-23.301, Time=0.56 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=29.759, Time=0.28 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-23.262, Time=0.93 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=-23.246, Time=0.96 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 6.766 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country MX Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=237.391, Time=0.24 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=462.453, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=173.540, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=11.624, Time=0.41 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=231.915, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=13.394, Time=0.55 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=13.406, Time=0.89 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=110.785, Time=0.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=15.246, Time=1.17 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=235.456, Time=0.18 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=13.548, Time=0.47 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=13.567, Time=0.59 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=78.799, Time=0.27 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=12.939, Time=1.03 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=13.771, Time=0.78 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 7.201 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country MX Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=236.211, Time=0.24 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=509.640, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=193.279, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=6.256, Time=0.30 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=256.042, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=8.190, Time=0.50 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=8.193, Time=0.58 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=121.246, Time=0.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=9.983, Time=1.28 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=234.224, Time=0.25 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=8.059, Time=0.60 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=8.102, Time=0.51 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=75.484, Time=0.26 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=7.371, Time=1.05 sec ARIMA(0,1,1)(0,1,1)[7] intercept : AIC=8.199, Time=1.50 sec Best model: ARIMA(0,1,1)(0,1,1)[7] Total fit time: 7.697 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country MX Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=414.767, Time=0.27 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=697.900, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=348.011, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=130.013, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=384.676, Time=0.13 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=131.884, Time=0.59 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=131.887, Time=0.75 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=250.143, Time=0.27 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=133.862, Time=2.03 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=412.787, Time=0.28 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=128.551, Time=0.48 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=385.670, Time=0.19 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=130.196, Time=0.69 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=130.201, Time=0.97 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=251.939, Time=0.25 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=132.189, Time=2.20 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=221.458, Time=0.34 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=128.047, Time=0.69 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=371.618, Time=0.26 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=129.865, Time=0.80 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=129.867, Time=2.09 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=242.451, Time=0.48 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=131.859, Time=2.85 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=180.999, Time=0.41 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=130.040, Time=1.35 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=128.858, Time=1.32 sec ARIMA(2,1,1)(0,1,1)[7] intercept : AIC=129.873, Time=1.85 sec Best model: ARIMA(2,1,1)(0,1,1)[7] Total fit time: 22.109 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country MX Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.56 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-103.394, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-334.179, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-418.274, Time=0.36 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-259.568, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.96 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.90 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-344.778, Time=0.19 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.17 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.28 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-419.989, Time=0.61 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-264.995, Time=0.10 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.50 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.62 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-350.134, Time=0.37 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.61 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-413.022, Time=0.33 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-418.806, Time=0.84 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-442.383, Time=1.13 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-268.165, Time=0.22 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.34 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=3.03 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-354.517, Time=0.53 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-442.304, Time=4.06 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-420.816, Time=0.79 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-443.174, Time=1.82 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-269.845, Time=0.28 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=2.18 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=3.73 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-352.573, Time=0.96 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=inf, Time=4.02 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=-417.508, Time=2.12 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 39.890 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country NL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.46 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-95.804, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-334.016, Time=0.17 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-427.753, Time=0.39 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-258.256, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.62 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.13 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-346.725, Time=0.20 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.26 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.31 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-429.657, Time=0.50 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-262.101, Time=0.12 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.01 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=1.62 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-351.711, Time=0.46 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.31 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-422.838, Time=0.39 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-428.083, Time=0.79 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-452.698, Time=0.82 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.54 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.68 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=inf, Time=2.54 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-354.499, Time=0.82 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=inf, Time=3.89 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-430.249, Time=0.42 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-453.521, Time=2.34 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=inf, Time=0.67 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=2.03 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=inf, Time=3.87 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-352.621, Time=1.36 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-451.617, Time=4.30 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=-390.857, Time=3.69 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 41.819 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country NL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.35 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-117.000, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-362.699, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-460.581, Time=0.37 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-286.336, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.00 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-463.808, Time=0.88 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.42 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=inf, Time=1.09 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-465.770, Time=1.71 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-462.816, Time=0.75 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.65 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-467.857, Time=1.62 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-381.273, Time=0.32 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.18 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-290.438, Time=0.12 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-423.900, Time=0.97 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=inf, Time=3.66 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-458.316, Time=0.67 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-466.453, Time=1.59 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.66 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-468.506, Time=0.95 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-463.363, Time=0.59 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=-382.066, Time=0.27 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=2.03 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=3.20 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=-291.835, Time=0.16 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-466.452, Time=1.60 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-424.502, Time=0.65 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=-468.977, Time=3.90 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=inf, Time=3.06 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=inf, Time=4.01 sec ARIMA(0,1,2)(2,1,2)[7] intercept : AIC=inf, Time=4.68 sec Best model: ARIMA(0,1,2)(2,1,2)[7] Total fit time: 49.408 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country NL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.59 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-118.132, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-333.638, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-419.209, Time=0.81 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-229.228, Time=0.17 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.74 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=1.38 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-325.803, Time=0.26 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.67 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.39 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-424.301, Time=0.92 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-235.587, Time=0.16 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.34 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=inf, Time=2.60 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-334.020, Time=0.36 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.95 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-426.298, Time=0.76 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-227.350, Time=0.13 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.89 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=inf, Time=1.56 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=inf, Time=2.73 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-424.302, Time=0.59 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-422.616, Time=1.22 sec ARIMA(1,1,0)(0,1,1)[7] intercept : AIC=-424.301, Time=0.78 sec Best model: ARIMA(1,1,0)(0,1,1)[7] Total fit time: 25.253 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country NL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.79 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-127.242, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-322.792, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.54 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-233.766, Time=0.07 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-374.248, Time=0.56 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.84 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.65 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-314.153, Time=0.26 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-372.248, Time=1.09 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-372.248, Time=0.87 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-363.763, Time=0.45 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-370.951, Time=1.08 sec ARIMA(1,1,0)(2,1,0)[7] intercept : AIC=-372.418, Time=1.44 sec Best model: ARIMA(1,1,0)(2,1,0)[7] Total fit time: 9.867 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country NL Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=582.381, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=382.181, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=178.075, Time=0.41 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=402.595, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=179.604, Time=0.58 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=179.636, Time=0.90 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=290.059, Time=0.29 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=181.148, Time=2.29 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.20 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=179.182, Time=0.63 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=178.816, Time=0.68 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=251.636, Time=0.32 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=175.853, Time=1.41 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=397.296, Time=0.29 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=177.845, Time=1.24 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=177.845, Time=2.16 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=294.058, Time=0.32 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=179.828, Time=2.63 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=170.762, Time=1.67 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=399.203, Time=0.34 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=172.601, Time=1.34 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=172.611, Time=2.56 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=289.060, Time=0.57 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=174.516, Time=3.97 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=175.279, Time=0.69 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=173.823, Time=2.09 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 28.204 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country NO Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=606.781, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=403.831, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=187.412, Time=0.42 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=426.984, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=188.678, Time=0.52 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=188.715, Time=0.78 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=310.006, Time=0.16 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.18 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.26 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=187.872, Time=0.72 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=187.325, Time=0.58 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=418.255, Time=0.15 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=inf, Time=0.63 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=188.350, Time=1.42 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=309.050, Time=0.29 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=inf, Time=2.86 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=186.520, Time=1.03 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.64 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=188.496, Time=1.47 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=188.496, Time=2.25 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=inf, Time=1.18 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=190.520, Time=3.30 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=180.406, Time=1.65 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=422.695, Time=0.52 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=182.391, Time=1.98 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=182.392, Time=3.31 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=309.543, Time=0.93 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=184.379, Time=4.00 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=184.757, Time=0.66 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=inf, Time=2.05 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 36.580 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country NO Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.33 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=623.952, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=414.572, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=190.739, Time=0.44 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=436.244, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=191.762, Time=0.53 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=191.812, Time=0.80 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=317.417, Time=0.17 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.06 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.25 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=191.776, Time=0.53 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=191.436, Time=0.60 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=268.663, Time=0.35 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=189.147, Time=1.13 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.76 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=191.082, Time=1.29 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=191.084, Time=2.49 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=inf, Time=1.15 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=193.147, Time=2.69 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=184.152, Time=1.65 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=431.044, Time=0.40 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=186.152, Time=1.85 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=186.152, Time=3.57 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=317.656, Time=0.92 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=188.110, Time=3.88 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=188.763, Time=0.66 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=inf, Time=2.12 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 30.955 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country NO Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.37 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=655.759, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=434.080, Time=0.16 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=189.283, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=449.024, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=190.066, Time=0.69 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=190.088, Time=0.94 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=329.070, Time=0.17 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=192.047, Time=1.72 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.23 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=190.624, Time=0.67 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=190.403, Time=0.63 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=272.771, Time=0.33 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=186.913, Time=1.08 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.51 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=188.818, Time=1.41 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=188.817, Time=2.47 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=inf, Time=1.15 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=190.858, Time=3.84 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=inf, Time=1.41 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=187.874, Time=0.68 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=190.547, Time=2.15 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 21.212 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country NO Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.38 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=675.155, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=447.156, Time=0.18 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=193.226, Time=0.47 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=456.903, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.56 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=inf, Time=0.97 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=335.936, Time=0.16 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.92 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=inf, Time=0.25 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=194.772, Time=0.68 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=194.596, Time=0.64 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=281.351, Time=0.32 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=188.963, Time=1.04 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=inf, Time=0.57 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=190.725, Time=1.65 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=190.722, Time=3.62 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=339.915, Time=0.38 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=192.721, Time=4.75 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=inf, Time=1.59 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=190.740, Time=1.71 sec ARIMA(1,1,2)(0,1,1)[7] intercept : AIC=193.766, Time=2.19 sec Best model: ARIMA(1,1,2)(0,1,1)[7] Total fit time: 24.196 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country NO Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1464.247, Time=0.39 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-1267.802, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1414.267, Time=0.24 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1474.038, Time=0.46 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1331.215, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1481.304, Time=0.88 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1406.697, Time=0.30 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.53 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.88 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1479.308, Time=1.23 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-1437.550, Time=0.67 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1478.220, Time=1.69 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1488.377, Time=1.34 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1480.058, Time=1.07 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-1412.473, Time=0.48 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-1487.494, Time=2.15 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-1487.516, Time=2.05 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-1339.232, Time=0.15 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1486.214, Time=1.38 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-1442.065, Time=1.15 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-1485.134, Time=2.29 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1488.871, Time=0.80 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1479.828, Time=0.47 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.18 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=inf, Time=2.44 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-1339.914, Time=0.05 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1486.175, Time=0.98 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-1444.056, Time=0.69 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-1485.816, Time=1.55 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-1490.735, Time=1.35 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-1483.840, Time=0.53 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-1412.633, Time=0.81 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=1.98 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=-1487.214, Time=2.34 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-1340.194, Time=0.05 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-1489.405, Time=2.31 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-1442.073, Time=0.75 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-1487.231, Time=2.51 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.65 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-1491.816, Time=1.78 sec ARIMA(2,1,0)(0,1,1)[7] intercept : AIC=-1483.001, Time=1.22 sec ARIMA(2,1,0)(1,1,0)[7] intercept : AIC=-1410.641, Time=0.99 sec ARIMA(2,1,0)(2,1,1)[7] intercept : AIC=inf, Time=3.27 sec ARIMA(2,1,0)(1,1,2)[7] intercept : AIC=-1484.430, Time=3.19 sec ARIMA(2,1,0)(0,1,0)[7] intercept : AIC=-1338.212, Time=0.14 sec ARIMA(2,1,0)(0,1,2)[7] intercept : AIC=-1489.806, Time=2.81 sec ARIMA(2,1,0)(2,1,0)[7] intercept : AIC=-1440.077, Time=1.98 sec ARIMA(2,1,0)(2,1,2)[7] intercept : AIC=inf, Time=3.47 sec ARIMA(1,1,0)(1,1,1)[7] intercept : AIC=inf, Time=1.23 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=inf, Time=2.08 sec ARIMA(1,1,1)(1,1,1)[7] intercept : AIC=inf, Time=1.71 sec Best model: ARIMA(2,1,0)(1,1,1)[7] intercept Total fit time: 68.812 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country RU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1515.405, Time=0.52 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-1308.518, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1459.399, Time=0.26 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1529.627, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1381.584, Time=0.15 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1538.776, Time=1.03 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1453.518, Time=0.33 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.73 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.99 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1537.297, Time=1.24 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-1492.911, Time=0.92 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1534.844, Time=2.30 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1545.621, Time=1.43 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1535.433, Time=0.74 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-1459.120, Time=0.46 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.14 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.56 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-1389.276, Time=0.20 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1544.129, Time=1.72 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-1497.286, Time=1.49 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-1541.656, Time=2.92 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1547.183, Time=0.73 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1536.395, Time=0.40 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.96 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=inf, Time=2.38 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-1388.047, Time=0.06 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1545.326, Time=1.87 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-1499.068, Time=0.60 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-1543.251, Time=1.42 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-1546.367, Time=1.44 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.52 sec ARIMA(1,1,0)(1,1,1)[7] intercept : AIC=inf, Time=2.05 sec Best model: ARIMA(1,1,0)(1,1,1)[7] Total fit time: 39.078 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country RU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1567.865, Time=0.46 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-1341.702, Time=0.07 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1502.990, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1579.556, Time=0.45 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1409.676, Time=0.14 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1585.003, Time=1.00 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1498.196, Time=0.30 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.83 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=1.90 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1583.579, Time=1.52 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-1536.990, Time=0.41 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1581.454, Time=1.94 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1590.146, Time=2.16 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1583.879, Time=0.94 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-1502.256, Time=0.42 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.99 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.54 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-1416.317, Time=0.17 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1588.675, Time=1.85 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-1540.008, Time=1.45 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-1586.521, Time=2.99 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1591.332, Time=0.81 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1584.814, Time=0.52 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.33 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=inf, Time=2.19 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-1415.839, Time=0.08 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1589.590, Time=1.54 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-1541.854, Time=0.64 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-1587.829, Time=2.21 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-1591.753, Time=1.98 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-1586.230, Time=0.81 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-1503.494, Time=0.45 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.27 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=2.87 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-1418.529, Time=0.15 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-1590.845, Time=1.37 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-1540.162, Time=0.61 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-1587.926, Time=2.92 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-1633.317, Time=1.74 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=inf, Time=1.53 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-1503.475, Time=0.80 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=2.73 sec ARIMA(2,1,1)(1,1,2)[7] : AIC=inf, Time=3.45 sec ARIMA(2,1,1)(0,1,0)[7] : AIC=-1419.112, Time=0.31 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=2.67 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-1537.854, Time=1.08 sec ARIMA(2,1,1)(2,1,2)[7] : AIC=inf, Time=2.91 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=inf, Time=2.22 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=inf, Time=1.97 sec ARIMA(2,1,1)(1,1,1)[7] intercept : AIC=inf, Time=2.49 sec Best model: ARIMA(2,1,1)(1,1,1)[7] Total fit time: 73.499 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country RU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-1648.657, Time=0.52 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-1410.540, Time=0.09 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1574.052, Time=0.27 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1659.634, Time=0.47 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1482.267, Time=0.11 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-1668.104, Time=0.95 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-1568.676, Time=0.27 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.95 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.26 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1666.553, Time=1.22 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-1611.558, Time=0.73 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-1664.213, Time=1.82 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-1674.190, Time=1.65 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1664.905, Time=0.85 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-1573.302, Time=0.54 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.04 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.80 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-1488.893, Time=0.20 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1672.625, Time=1.98 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-1615.079, Time=1.31 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-1670.270, Time=1.68 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-1675.334, Time=0.89 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1665.440, Time=0.36 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.61 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=inf, Time=2.37 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=-1488.252, Time=0.07 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1673.397, Time=1.45 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-1616.985, Time=0.67 sec ARIMA(1,1,0)(2,1,2)[7] : AIC=-1671.480, Time=2.50 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=-1675.835, Time=1.59 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-1668.114, Time=0.90 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-1574.450, Time=0.44 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.37 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=3.04 sec ARIMA(2,1,0)(0,1,0)[7] : AIC=-1491.088, Time=0.21 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-1674.967, Time=2.10 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-1615.169, Time=0.71 sec ARIMA(2,1,0)(2,1,2)[7] : AIC=-1671.841, Time=2.38 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=1.85 sec ARIMA(2,1,0)(1,1,1)[7] intercept : AIC=-1674.318, Time=2.16 sec Best model: ARIMA(2,1,0)(1,1,1)[7] Total fit time: 53.399 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country RU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.64 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-1485.479, Time=0.11 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-1657.580, Time=0.28 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-1742.737, Time=0.48 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-1561.439, Time=0.09 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.07 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-1751.895, Time=1.87 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=inf, Time=2.21 sec ARIMA(0,1,0)(0,1,2)[7] : AIC=-1733.317, Time=0.97 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-1758.412, Time=1.85 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-1748.408, Time=0.96 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=inf, Time=2.56 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=2.50 sec ARIMA(1,1,0)(0,1,2)[7] : AIC=-1759.042, Time=1.51 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-1748.677, Time=0.44 sec ARIMA(1,1,0)(1,1,2)[7] : AIC=-1756.840, Time=2.08 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=1.02 sec ARIMA(2,1,0)(0,1,2)[7] : AIC=-1761.038, Time=2.44 sec ARIMA(2,1,0)(0,1,1)[7] : AIC=-1752.508, Time=0.63 sec ARIMA(2,1,0)(1,1,2)[7] : AIC=inf, Time=3.32 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.58 sec ARIMA(2,1,1)(0,1,2)[7] : AIC=inf, Time=3.20 sec ARIMA(2,1,0)(0,1,2)[7] intercept : AIC=-1760.276, Time=3.43 sec Best model: ARIMA(2,1,0)(0,1,2)[7] Total fit time: 35.252 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country RU Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.63 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=175.845, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-58.115, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=1.13 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=91.466, Time=0.06 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-87.805, Time=0.47 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=1.97 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=1.55 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=7.904, Time=0.22 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-98.975, Time=0.37 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-64.364, Time=0.25 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=3.03 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.19 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-103.447, Time=0.70 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-67.618, Time=0.47 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=3.03 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.02 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-105.411, Time=0.70 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-69.226, Time=0.31 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=2.74 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.20 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-105.786, Time=0.41 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-67.967, Time=0.20 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=2.66 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=0.89 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-105.544, Time=0.49 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-104.291, Time=1.12 sec ARIMA(0,1,1)(2,1,0)[7] intercept : AIC=-103.789, Time=1.18 sec Best model: ARIMA(0,1,1)(2,1,0)[7] Total fit time: 29.253 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country SG Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.61 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=170.328, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-74.465, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=1.01 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=82.075, Time=0.07 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-104.255, Time=0.52 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.20 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=1.12 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-3.583, Time=0.27 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-116.439, Time=0.46 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-81.498, Time=0.35 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=3.24 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.89 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-121.536, Time=0.84 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-85.214, Time=0.56 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=2.88 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.22 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-123.497, Time=0.69 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-86.820, Time=0.34 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.01 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.65 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-123.830, Time=0.45 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-85.439, Time=0.21 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=1.99 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.37 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-123.632, Time=0.50 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-122.298, Time=1.28 sec ARIMA(0,1,1)(2,1,0)[7] intercept : AIC=-121.835, Time=1.14 sec Best model: ARIMA(0,1,1)(2,1,0)[7] Total fit time: 31.125 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country SG Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=1.02 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=160.846, Time=0.08 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-95.896, Time=0.22 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.88 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=69.864, Time=0.07 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-127.708, Time=0.52 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.18 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=1.13 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-22.539, Time=0.27 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-140.403, Time=0.55 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-103.395, Time=0.39 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=3.81 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.43 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-145.657, Time=0.87 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-107.290, Time=0.55 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=3.47 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.37 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-147.618, Time=1.02 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-108.901, Time=0.30 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.43 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=1.59 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-147.881, Time=0.45 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-107.457, Time=0.17 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=2.78 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.58 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-147.756, Time=0.55 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-146.453, Time=1.16 sec ARIMA(0,1,1)(2,1,0)[7] intercept : AIC=-145.881, Time=1.08 sec Best model: ARIMA(0,1,1)(2,1,0)[7] Total fit time: 33.948 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country SG Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.63 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=150.194, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-115.700, Time=0.24 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=0.71 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=55.316, Time=0.06 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-149.322, Time=0.45 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=3.11 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=0.94 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-40.112, Time=0.29 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-161.498, Time=0.49 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-122.619, Time=0.39 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=2.93 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=2.11 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-166.403, Time=0.75 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-126.117, Time=0.49 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=3.11 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.34 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-168.382, Time=0.72 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-127.679, Time=0.34 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.06 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=2.10 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-168.422, Time=0.37 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-125.778, Time=0.18 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=inf, Time=2.46 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=inf, Time=1.21 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-168.522, Time=0.53 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=-127.310, Time=0.34 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=2.63 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=inf, Time=1.52 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-167.338, Time=1.45 sec ARIMA(0,1,2)(2,1,0)[7] intercept : AIC=-166.554, Time=1.35 sec Best model: ARIMA(0,1,2)(2,1,0)[7] Total fit time: 37.325 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country SG Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=inf, Time=0.48 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=142.596, Time=0.06 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-125.253, Time=0.23 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=inf, Time=1.40 sec ARIMA(1,1,0)(0,1,0)[7] : AIC=48.705, Time=0.07 sec ARIMA(1,1,0)(2,1,0)[7] : AIC=-160.407, Time=0.57 sec ARIMA(1,1,0)(2,1,1)[7] : AIC=inf, Time=2.43 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=inf, Time=1.39 sec ARIMA(0,1,0)(2,1,0)[7] : AIC=-54.859, Time=0.27 sec ARIMA(2,1,0)(2,1,0)[7] : AIC=-169.579, Time=0.46 sec ARIMA(2,1,0)(1,1,0)[7] : AIC=-129.855, Time=0.32 sec ARIMA(2,1,0)(2,1,1)[7] : AIC=inf, Time=3.03 sec ARIMA(2,1,0)(1,1,1)[7] : AIC=inf, Time=1.66 sec ARIMA(2,1,1)(2,1,0)[7] : AIC=-172.339, Time=0.96 sec ARIMA(2,1,1)(1,1,0)[7] : AIC=-131.430, Time=0.44 sec ARIMA(2,1,1)(2,1,1)[7] : AIC=inf, Time=2.98 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=inf, Time=2.19 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-174.325, Time=0.71 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-133.130, Time=0.64 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=inf, Time=3.35 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=inf, Time=2.23 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-174.109, Time=0.32 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-173.278, Time=1.81 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-174.496, Time=0.56 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=-132.769, Time=0.32 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=inf, Time=3.09 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=inf, Time=2.03 sec ARIMA(0,1,2)(2,1,0)[7] intercept : AIC=-172.498, Time=1.46 sec Best model: ARIMA(0,1,2)(2,1,0)[7] Total fit time: 35.512 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country SG Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-538.475, Time=0.59 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-370.434, Time=0.10 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-565.044, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-624.394, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-492.697, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-632.467, Time=0.60 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-560.116, Time=0.24 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-630.761, Time=1.07 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-631.022, Time=2.02 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-631.429, Time=0.76 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-589.693, Time=0.45 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-628.659, Time=2.29 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-640.337, Time=0.75 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-633.876, Time=0.53 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-570.844, Time=0.37 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-638.635, Time=1.83 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-639.160, Time=2.22 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-501.227, Time=0.15 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-639.517, Time=1.57 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-601.021, Time=1.21 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-636.505, Time=2.45 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-635.747, Time=0.56 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-639.997, Time=1.26 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-649.272, Time=1.36 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-648.320, Time=0.89 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-577.314, Time=0.60 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-647.335, Time=2.69 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-647.327, Time=3.11 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-505.394, Time=0.28 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-649.131, Time=2.50 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-609.989, Time=1.11 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-645.388, Time=3.23 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-643.843, Time=0.83 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-636.398, Time=1.38 sec ARIMA(1,1,2)(1,1,1)[7] intercept : AIC=-640.083, Time=2.10 sec Best model: ARIMA(1,1,2)(1,1,1)[7] Total fit time: 41.720 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #1 of country US Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-493.426, Time=0.34 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-339.395, Time=0.05 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-539.253, Time=0.20 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-591.903, Time=0.35 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-473.248, Time=0.07 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-598.510, Time=0.56 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-536.431, Time=0.22 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-596.987, Time=1.45 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-597.319, Time=1.94 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-597.457, Time=0.74 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-562.683, Time=0.50 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-594.511, Time=1.17 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-605.786, Time=0.75 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-601.404, Time=0.51 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-546.832, Time=0.39 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-604.139, Time=1.98 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-604.518, Time=2.36 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-480.630, Time=0.12 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-605.127, Time=1.04 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-573.631, Time=0.74 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-601.786, Time=1.39 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-600.087, Time=0.42 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-604.586, Time=0.89 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-608.719, Time=1.49 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-608.328, Time=1.09 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-548.201, Time=0.62 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-606.787, Time=2.47 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-606.814, Time=3.00 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-480.678, Time=0.26 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-608.606, Time=2.34 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-575.763, Time=0.79 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-604.727, Time=3.32 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-607.254, Time=0.74 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-608.355, Time=1.93 sec ARIMA(1,1,2)(1,1,1)[7] intercept : AIC=-606.657, Time=2.59 sec Best model: ARIMA(1,1,2)(1,1,1)[7] Total fit time: 38.871 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #2 of country US Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-447.282, Time=0.30 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-256.828, Time=0.04 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-523.604, Time=0.21 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-574.313, Time=0.34 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-426.589, Time=0.06 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-579.100, Time=0.47 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-510.612, Time=0.28 sec ARIMA(0,1,1)(2,1,1)[7] : AIC=-577.348, Time=1.13 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-577.319, Time=1.50 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-578.458, Time=0.87 sec ARIMA(0,1,1)(2,1,0)[7] : AIC=-539.267, Time=0.43 sec ARIMA(0,1,1)(2,1,2)[7] : AIC=-575.387, Time=2.32 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-595.846, Time=0.59 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-592.289, Time=0.51 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-531.519, Time=0.39 sec ARIMA(1,1,1)(2,1,1)[7] : AIC=-593.976, Time=1.51 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-593.961, Time=2.02 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-446.927, Time=0.13 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-595.427, Time=0.94 sec ARIMA(1,1,1)(2,1,0)[7] : AIC=-560.234, Time=0.76 sec ARIMA(1,1,1)(2,1,2)[7] : AIC=-592.006, Time=3.08 sec ARIMA(1,1,0)(1,1,1)[7] : AIC=-589.731, Time=0.41 sec ARIMA(2,1,1)(1,1,1)[7] : AIC=-594.119, Time=1.28 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-596.138, Time=1.60 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-595.974, Time=1.38 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-531.836, Time=0.75 sec ARIMA(1,1,2)(2,1,1)[7] : AIC=-594.228, Time=2.74 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-594.187, Time=3.21 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-453.592, Time=0.26 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-595.839, Time=2.68 sec ARIMA(1,1,2)(2,1,0)[7] : AIC=-561.364, Time=1.45 sec ARIMA(1,1,2)(2,1,2)[7] : AIC=-592.222, Time=3.51 sec ARIMA(0,1,2)(1,1,1)[7] : AIC=-597.795, Time=0.75 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-595.032, Time=0.50 sec ARIMA(0,1,2)(1,1,0)[7] : AIC=-533.467, Time=0.33 sec ARIMA(0,1,2)(2,1,1)[7] : AIC=-595.906, Time=1.19 sec ARIMA(0,1,2)(1,1,2)[7] : AIC=-595.892, Time=2.05 sec ARIMA(0,1,2)(0,1,0)[7] : AIC=-446.976, Time=0.15 sec ARIMA(0,1,2)(0,1,2)[7] : AIC=-597.464, Time=1.22 sec ARIMA(0,1,2)(2,1,0)[7] : AIC=-562.784, Time=0.46 sec ARIMA(0,1,2)(2,1,2)[7] : AIC=-593.938, Time=3.48 sec ARIMA(0,1,2)(1,1,1)[7] intercept : AIC=-596.151, Time=1.98 sec Best model: ARIMA(0,1,2)(1,1,1)[7] Total fit time: 49.319 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #3 of country US Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-330.903, Time=0.21 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-157.533, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-449.851, Time=0.22 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-487.496, Time=0.33 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-347.136, Time=0.08 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-485.675, Time=0.51 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-485.668, Time=0.67 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-446.725, Time=0.25 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-487.383, Time=1.39 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-332.345, Time=0.17 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-503.580, Time=0.52 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-361.854, Time=0.14 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-501.720, Time=0.78 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-501.720, Time=0.88 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-461.796, Time=0.38 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-502.958, Time=2.06 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-492.280, Time=0.27 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=inf, Time=1.88 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-509.007, Time=1.21 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-373.970, Time=0.25 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-507.241, Time=1.57 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-507.249, Time=2.43 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-460.129, Time=0.63 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=inf, Time=3.50 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-504.198, Time=0.46 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-509.651, Time=1.64 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-372.448, Time=0.46 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-507.702, Time=1.62 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-507.742, Time=2.63 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-460.505, Time=1.20 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=inf, Time=3.71 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=-497.664, Time=1.23 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 33.376 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #4 of country US Performing stepwise search to minimize aic ARIMA(0,1,0)(1,1,1)[7] : AIC=-332.103, Time=0.26 sec ARIMA(0,1,0)(0,1,0)[7] : AIC=-169.595, Time=0.03 sec ARIMA(1,1,0)(1,1,0)[7] : AIC=-467.371, Time=0.23 sec ARIMA(0,1,1)(0,1,1)[7] : AIC=-502.998, Time=0.29 sec ARIMA(0,1,1)(0,1,0)[7] : AIC=-371.881, Time=0.10 sec ARIMA(0,1,1)(1,1,1)[7] : AIC=-501.001, Time=0.44 sec ARIMA(0,1,1)(0,1,2)[7] : AIC=-501.002, Time=0.59 sec ARIMA(0,1,1)(1,1,0)[7] : AIC=-468.927, Time=0.26 sec ARIMA(0,1,1)(1,1,2)[7] : AIC=-502.222, Time=1.47 sec ARIMA(0,1,0)(0,1,1)[7] : AIC=-332.184, Time=0.14 sec ARIMA(1,1,1)(0,1,1)[7] : AIC=-518.802, Time=0.46 sec ARIMA(1,1,1)(0,1,0)[7] : AIC=-388.851, Time=0.15 sec ARIMA(1,1,1)(1,1,1)[7] : AIC=-516.802, Time=0.65 sec ARIMA(1,1,1)(0,1,2)[7] : AIC=-516.802, Time=0.92 sec ARIMA(1,1,1)(1,1,0)[7] : AIC=-483.823, Time=0.35 sec ARIMA(1,1,1)(1,1,2)[7] : AIC=-517.844, Time=1.99 sec ARIMA(1,1,0)(0,1,1)[7] : AIC=-501.451, Time=0.26 sec ARIMA(2,1,1)(0,1,1)[7] : AIC=-517.028, Time=1.05 sec ARIMA(1,1,2)(0,1,1)[7] : AIC=-523.736, Time=1.33 sec ARIMA(1,1,2)(0,1,0)[7] : AIC=-402.583, Time=0.28 sec ARIMA(1,1,2)(1,1,1)[7] : AIC=-513.421, Time=1.65 sec ARIMA(1,1,2)(0,1,2)[7] : AIC=-513.054, Time=1.68 sec ARIMA(1,1,2)(1,1,0)[7] : AIC=-481.942, Time=0.75 sec ARIMA(1,1,2)(1,1,2)[7] : AIC=-513.858, Time=2.71 sec ARIMA(0,1,2)(0,1,1)[7] : AIC=-520.699, Time=0.46 sec ARIMA(2,1,2)(0,1,1)[7] : AIC=-523.780, Time=1.40 sec ARIMA(2,1,2)(0,1,0)[7] : AIC=-401.273, Time=0.56 sec ARIMA(2,1,2)(1,1,1)[7] : AIC=-522.053, Time=1.70 sec ARIMA(2,1,2)(0,1,2)[7] : AIC=-522.092, Time=2.48 sec ARIMA(2,1,2)(1,1,0)[7] : AIC=-479.823, Time=0.56 sec ARIMA(2,1,2)(1,1,2)[7] : AIC=-521.358, Time=3.38 sec ARIMA(2,1,2)(0,1,1)[7] intercept : AIC=-521.635, Time=2.65 sec Best model: ARIMA(2,1,2)(0,1,1)[7] Total fit time: 31.265 seconds
/Users/parkj/opt/anaconda3/envs/pylearn/lib/python3.9/site-packages/statsmodels/base/model.py:604: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals
warnings.warn("Maximum Likelihood optimization failed to "
Completed fold #5 of country US
rez_country_srm_7d = {'train':rez_country_srm_7d_train, 'validation':rez_country_srm_7d_val, 'test':rez_country_srm_7d_test}
filePath_pickle = Path('/Users/parkj/Documents/pyDat/dataSet/covid19_country_srm_7d_with_lagging.pickle')
with open(filePath_pickle, 'wb') as f:
pickle.dump(rez_country_srm_7d, f)
filePath_pickle = Path('/Users/parkj/Documents/pyDat/dataSet/covid19_country_srm_7d_with_lagging.pickle')
with open(filePath_pickle, 'rb') as f:
rez_country_srm_7d = pickle.load(f)
plot_actual_predicted(rez_country_srm_7d['validation'], dict_country, 'val', n_steps_out=7)